update model card README.md
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README.md
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| 1 |
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---
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tags:
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- summarization
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1
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This model is a fine-tuned version of [Ameer05/model-token-repo](https://huggingface.co/Ameer05/model-token-repo) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.6315
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- Rouge1: 61.441
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- Rouge2: 52.9403
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- Rougel: 58.3426
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- Rougelsum: 60.8249
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 100
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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| No log | 0.91 | 5 | 2.0139 | 53.4301 | 46.6698 | 50.644 | 53.3985 |
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| 58 |
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| No log | 1.91 | 10 | 1.6309 | 61.4629 | 53.8884 | 59.0867 | 60.8823 |
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| No log | 2.91 | 15 | 1.5379 | 61.2938 | 53.7208 | 59.0644 | 60.7381 |
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| 60 |
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| No log | 3.91 | 20 | 1.4470 | 63.2667 | 55.9273 | 60.5112 | 62.7538 |
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| 61 |
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| 1.5454 | 4.91 | 25 | 1.4353 | 62.7166 | 54.8328 | 60.0101 | 62.1378 |
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| 62 |
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| 1.5454 | 5.91 | 30 | 1.4411 | 59.7469 | 51.9068 | 57.036 | 58.9474 |
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| 63 |
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| 1.5454 | 6.91 | 35 | 1.5195 | 64.152 | 57.1447 | 61.362 | 63.5951 |
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| 1.5454 | 7.91 | 40 | 1.6174 | 60.1464 | 51.5654 | 57.1676 | 59.4405 |
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| 0.5429 | 8.91 | 45 | 1.7451 | 61.9696 | 53.6421 | 58.5884 | 61.3286 |
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| 66 |
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| 0.5429 | 9.91 | 50 | 1.9081 | 60.3296 | 52.3052 | 57.6518 | 59.7854 |
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| 67 |
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| 0.5429 | 10.91 | 55 | 1.9721 | 61.5597 | 51.9027 | 57.1184 | 60.6717 |
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| 68 |
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| 0.5429 | 11.91 | 60 | 2.0471 | 61.2222 | 53.9475 | 58.725 | 60.6668 |
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| 69 |
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| 0.5429 | 12.91 | 65 | 2.1422 | 60.1915 | 52.0627 | 56.9955 | 59.438 |
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| 0.1506 | 13.91 | 70 | 2.1542 | 61.6915 | 53.045 | 58.1727 | 60.8765 |
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| 71 |
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| 0.1506 | 14.91 | 75 | 2.1885 | 59.8069 | 51.6543 | 56.8112 | 59.2055 |
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| 0.1506 | 15.91 | 80 | 2.3146 | 61.695 | 53.2666 | 57.9003 | 61.1108 |
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| 73 |
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| 0.1506 | 16.91 | 85 | 2.3147 | 60.4482 | 52.1694 | 57.0649 | 59.7882 |
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| 74 |
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| 0.0452 | 17.91 | 90 | 2.1731 | 60.0259 | 51.5046 | 56.7399 | 59.2955 |
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| 0.0452 | 18.91 | 95 | 2.2690 | 60.0534 | 52.4819 | 57.1631 | 59.5056 |
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| 0.0452 | 19.91 | 100 | 2.2990 | 58.0737 | 48.8098 | 54.5684 | 57.3187 |
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| 0.0452 | 20.91 | 105 | 2.2704 | 61.8982 | 53.9077 | 58.6909 | 61.4252 |
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| 78 |
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| 0.0267 | 21.91 | 110 | 2.3012 | 62.0174 | 53.5427 | 58.5278 | 61.1921 |
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| 0.0267 | 22.91 | 115 | 2.3569 | 61.6327 | 53.7387 | 58.8908 | 61.1623 |
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| 0.0267 | 23.91 | 120 | 2.3579 | 60.228 | 52.3747 | 58.1448 | 59.7322 |
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| 0.0267 | 24.91 | 125 | 2.3389 | 60.4902 | 51.7935 | 57.0689 | 59.7132 |
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| 0.0267 | 25.91 | 130 | 2.3168 | 58.8469 | 50.3181 | 55.7386 | 58.3598 |
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| 0.0211 | 26.91 | 135 | 2.4147 | 59.4225 | 50.8405 | 56.503 | 58.7221 |
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| 0.0211 | 27.91 | 140 | 2.3631 | 59.7489 | 51.2137 | 57.3204 | 59.3348 |
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| 85 |
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| 0.0211 | 28.91 | 145 | 2.3850 | 60.1718 | 51.4176 | 57.2152 | 59.5157 |
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| 86 |
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| 0.0211 | 29.91 | 150 | 2.4610 | 60.1433 | 51.433 | 56.6256 | 59.3265 |
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| 87 |
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| 0.0175 | 30.91 | 155 | 2.4400 | 58.8345 | 49.7031 | 55.3079 | 57.9236 |
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| 88 |
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| 0.0175 | 31.91 | 160 | 2.4506 | 59.209 | 50.1626 | 55.6451 | 58.5791 |
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| 89 |
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| 0.0175 | 32.91 | 165 | 2.4316 | 59.7713 | 50.8999 | 56.4235 | 58.9845 |
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| 90 |
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| 0.0175 | 33.91 | 170 | 2.2781 | 60.1822 | 51.9435 | 57.4586 | 59.6766 |
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| 91 |
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| 0.0175 | 34.91 | 175 | 2.3849 | 58.2328 | 49.2106 | 55.1516 | 57.5072 |
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| 92 |
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| 0.0141 | 35.91 | 180 | 2.4872 | 58.4916 | 50.3345 | 55.5991 | 58.1131 |
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| 93 |
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| 0.0141 | 36.91 | 185 | 2.4883 | 59.0957 | 49.76 | 55.3567 | 58.076 |
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| 94 |
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| 0.0141 | 37.91 | 190 | 2.4327 | 58.091 | 48.8628 | 54.8678 | 57.5406 |
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| 95 |
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| 0.0141 | 38.91 | 195 | 2.4998 | 57.7428 | 48.7366 | 54.2166 | 56.7643 |
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| 96 |
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| 0.0089 | 39.91 | 200 | 2.4107 | 60.1662 | 51.9832 | 57.1372 | 59.6989 |
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| 97 |
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| 0.0089 | 40.91 | 205 | 2.4700 | 58.2159 | 49.3934 | 54.9265 | 57.4126 |
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| 98 |
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| 0.0089 | 41.91 | 210 | 2.4833 | 58.7434 | 49.6619 | 55.5239 | 57.9562 |
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| 99 |
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| 0.0089 | 42.91 | 215 | 2.4703 | 60.2984 | 51.3168 | 56.9082 | 59.3958 |
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| 100 |
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| 0.0062 | 43.91 | 220 | 2.5306 | 60.5455 | 52.1189 | 57.3213 | 60.0232 |
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| 101 |
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| 0.0062 | 44.91 | 225 | 2.5181 | 60.2149 | 51.2187 | 56.1935 | 59.3471 |
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| 102 |
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| 0.0062 | 45.91 | 230 | 2.4871 | 59.8013 | 51.6114 | 56.0911 | 59.0902 |
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| 103 |
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| 0.0062 | 46.91 | 235 | 2.4811 | 58.0271 | 48.9441 | 54.3108 | 57.3647 |
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| 104 |
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| 0.0062 | 47.91 | 240 | 2.5290 | 62.5087 | 54.6149 | 59.638 | 62.0455 |
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| 105 |
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| 0.0072 | 48.91 | 245 | 2.5194 | 58.7193 | 49.9679 | 55.6517 | 58.1569 |
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| 106 |
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| 0.0072 | 49.91 | 250 | 2.5708 | 58.4626 | 49.5257 | 54.5032 | 58.1413 |
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| 107 |
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| 0.0072 | 50.91 | 255 | 2.6449 | 58.446 | 49.4625 | 55.1092 | 58.03 |
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| 108 |
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| 0.0072 | 51.91 | 260 | 2.5592 | 58.859 | 49.4398 | 55.1503 | 57.9663 |
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| 109 |
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| 0.0056 | 52.91 | 265 | 2.5086 | 59.7322 | 51.3051 | 56.5401 | 59.2726 |
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| 110 |
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| 0.0056 | 53.91 | 270 | 2.4846 | 57.8603 | 48.2408 | 54.3847 | 57.115 |
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| 111 |
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| 0.0056 | 54.91 | 275 | 2.5509 | 58.9506 | 50.045 | 55.6658 | 58.3618 |
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| 112 |
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| 0.0056 | 55.91 | 280 | 2.5032 | 60.2524 | 51.8167 | 56.98 | 59.7506 |
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| 113 |
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| 0.0056 | 56.91 | 285 | 2.5012 | 60.0596 | 51.4924 | 56.7181 | 59.5037 |
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| 114 |
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| 0.0054 | 57.91 | 290 | 2.5176 | 61.0622 | 52.6235 | 57.9317 | 60.5036 |
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| 115 |
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| 0.0054 | 58.91 | 295 | 2.5024 | 62.9246 | 54.8544 | 59.9824 | 62.5584 |
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| 116 |
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| 0.0054 | 59.91 | 300 | 2.5687 | 62.2602 | 53.9673 | 58.9862 | 61.5837 |
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| 117 |
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| 0.0054 | 60.91 | 305 | 2.5890 | 62.5706 | 54.227 | 59.2032 | 62.125 |
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| 118 |
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| 0.0036 | 61.91 | 310 | 2.5454 | 62.1565 | 53.2585 | 58.7169 | 61.3943 |
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| 119 |
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| 0.0036 | 62.91 | 315 | 2.5629 | 62.8292 | 54.6781 | 59.9889 | 62.254 |
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| 120 |
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| 0.0036 | 63.91 | 320 | 2.5581 | 58.8394 | 50.4421 | 56.0742 | 58.1945 |
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| 121 |
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| 0.0036 | 64.91 | 325 | 2.5532 | 59.5814 | 51.1335 | 56.5841 | 59.196 |
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| 122 |
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| 0.0031 | 65.91 | 330 | 2.5826 | 59.0485 | 50.3992 | 55.5283 | 58.3757 |
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| 123 |
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| 0.0031 | 66.91 | 335 | 2.5815 | 61.4832 | 52.7977 | 57.7351 | 60.9888 |
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| 124 |
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| 0.0031 | 67.91 | 340 | 2.5865 | 61.7836 | 53.6797 | 58.6743 | 61.3765 |
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| 125 |
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| 0.0031 | 68.91 | 345 | 2.6007 | 61.2253 | 52.8781 | 57.7006 | 60.717 |
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| 126 |
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| 0.0031 | 69.91 | 350 | 2.6210 | 60.717 | 52.4933 | 57.5089 | 60.4196 |
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| 127 |
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| 0.0035 | 70.91 | 355 | 2.6169 | 61.3491 | 53.3932 | 58.2288 | 60.8793 |
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| 128 |
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| 0.0035 | 71.91 | 360 | 2.6025 | 62.0101 | 54.0289 | 59.0822 | 61.7202 |
|
| 129 |
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| 0.0035 | 72.91 | 365 | 2.5705 | 61.2227 | 52.9937 | 58.2493 | 60.6631 |
|
| 130 |
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| 0.0035 | 73.91 | 370 | 2.5623 | 59.1718 | 50.7827 | 56.1851 | 58.7118 |
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| 131 |
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| 0.002 | 74.91 | 375 | 2.5536 | 58.4201 | 49.6923 | 55.0398 | 57.7707 |
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| 132 |
+
| 0.002 | 75.91 | 380 | 2.5478 | 60.2307 | 51.7503 | 57.3173 | 59.692 |
|
| 133 |
+
| 0.002 | 76.91 | 385 | 2.6039 | 58.7637 | 49.741 | 55.5341 | 58.0784 |
|
| 134 |
+
| 0.002 | 77.91 | 390 | 2.6371 | 59.3929 | 50.6444 | 55.9887 | 58.813 |
|
| 135 |
+
| 0.002 | 78.91 | 395 | 2.6238 | 59.0572 | 50.605 | 55.6631 | 58.4366 |
|
| 136 |
+
| 0.0019 | 79.91 | 400 | 2.5783 | 57.9852 | 49.2588 | 54.822 | 57.4643 |
|
| 137 |
+
| 0.0019 | 80.91 | 405 | 2.5982 | 58.0218 | 49.1651 | 54.9876 | 57.4066 |
|
| 138 |
+
| 0.0019 | 81.91 | 410 | 2.6141 | 60.3133 | 51.5723 | 56.9476 | 59.715 |
|
| 139 |
+
| 0.0019 | 82.91 | 415 | 2.5904 | 60.8199 | 51.8956 | 58.406 | 60.323 |
|
| 140 |
+
| 0.0017 | 83.91 | 420 | 2.5718 | 60.3449 | 51.1433 | 57.6984 | 59.7513 |
|
| 141 |
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| 0.0017 | 84.91 | 425 | 2.5737 | 60.151 | 51.1986 | 57.3376 | 59.378 |
|
| 142 |
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| 0.0017 | 85.91 | 430 | 2.5807 | 60.9273 | 52.2469 | 58.2038 | 60.1642 |
|
| 143 |
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| 0.0017 | 86.91 | 435 | 2.5900 | 60.1846 | 51.6144 | 57.5407 | 59.5109 |
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| 144 |
+
| 0.0011 | 87.91 | 440 | 2.6066 | 62.0776 | 53.6022 | 59.157 | 61.6201 |
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| 145 |
+
| 0.0011 | 88.91 | 445 | 2.6231 | 61.8822 | 53.5232 | 58.965 | 61.401 |
|
| 146 |
+
| 0.0011 | 89.91 | 450 | 2.6273 | 60.3358 | 51.9941 | 57.3823 | 59.7729 |
|
| 147 |
+
| 0.0011 | 90.91 | 455 | 2.6194 | 60.0196 | 51.6134 | 57.1357 | 59.4594 |
|
| 148 |
+
| 0.0011 | 91.91 | 460 | 2.6118 | 60.6898 | 52.1328 | 57.3076 | 60.0351 |
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| 149 |
+
| 0.0015 | 92.91 | 465 | 2.6032 | 61.2119 | 52.5034 | 57.8098 | 60.6634 |
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| 150 |
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| 0.0015 | 93.91 | 470 | 2.6040 | 61.4812 | 52.8197 | 57.9668 | 60.8767 |
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| 151 |
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| 0.0015 | 94.91 | 475 | 2.6158 | 61.4046 | 52.8905 | 57.8958 | 60.804 |
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| 152 |
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| 0.0015 | 95.91 | 480 | 2.6280 | 62.1764 | 53.8521 | 58.8608 | 61.6138 |
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| 153 |
+
| 0.0012 | 96.91 | 485 | 2.6304 | 62.2028 | 53.8967 | 58.8976 | 61.6409 |
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| 154 |
+
| 0.0012 | 97.91 | 490 | 2.6328 | 61.7371 | 53.3908 | 58.4107 | 61.1382 |
|
| 155 |
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| 0.0012 | 98.91 | 495 | 2.6331 | 61.441 | 52.9403 | 58.3426 | 60.8249 |
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| 156 |
+
| 0.0012 | 99.91 | 500 | 2.6315 | 61.441 | 52.9403 | 58.3426 | 60.8249 |
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| 157 |
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| 158 |
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| 159 |
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### Framework versions
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| 160 |
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- Transformers 4.15.0
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| 162 |
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- Pytorch 1.9.1
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| 163 |
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- Datasets 1.18.4
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| 164 |
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- Tokenizers 0.10.3
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