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--- |
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base_model: vinai/phobert-base-v2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CS505-Classifier-T4_predictLabel_a1_v11 |
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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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# CS505-Classifier-T4_predictLabel_a1_v11 |
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0012 |
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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: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 70 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.98 | 48 | 0.6966 | |
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| No log | 1.96 | 96 | 0.3265 | |
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| No log | 2.94 | 144 | 0.2746 | |
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| No log | 3.92 | 192 | 0.1899 | |
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| No log | 4.9 | 240 | 0.1671 | |
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| No log | 5.88 | 288 | 0.1193 | |
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| No log | 6.86 | 336 | 0.1259 | |
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| No log | 7.84 | 384 | 0.0737 | |
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| No log | 8.82 | 432 | 0.0461 | |
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| No log | 9.8 | 480 | 0.0490 | |
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| 0.3023 | 10.78 | 528 | 0.0293 | |
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| 0.3023 | 11.76 | 576 | 0.0324 | |
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| 0.3023 | 12.73 | 624 | 0.0355 | |
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| 0.3023 | 13.71 | 672 | 0.0331 | |
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| 0.3023 | 14.69 | 720 | 0.0158 | |
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| 0.3023 | 15.67 | 768 | 0.0108 | |
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| 0.3023 | 16.65 | 816 | 0.0062 | |
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| 0.3023 | 17.63 | 864 | 0.0048 | |
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| 0.3023 | 18.61 | 912 | 0.0038 | |
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| 0.3023 | 19.59 | 960 | 0.0053 | |
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| 0.0241 | 20.57 | 1008 | 0.0077 | |
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| 0.0241 | 21.55 | 1056 | 0.0027 | |
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| 0.0241 | 22.53 | 1104 | 0.0025 | |
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| 0.0241 | 23.51 | 1152 | 0.0051 | |
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| 0.0241 | 24.49 | 1200 | 0.0088 | |
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| 0.0241 | 25.47 | 1248 | 0.0023 | |
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| 0.0241 | 26.45 | 1296 | 0.0023 | |
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| 0.0241 | 27.43 | 1344 | 0.0022 | |
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| 0.0241 | 28.41 | 1392 | 0.0018 | |
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| 0.0241 | 29.39 | 1440 | 0.0019 | |
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| 0.0241 | 30.37 | 1488 | 0.0018 | |
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| 0.0065 | 31.35 | 1536 | 0.0017 | |
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| 0.0065 | 32.33 | 1584 | 0.0033 | |
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| 0.0065 | 33.31 | 1632 | 0.0016 | |
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| 0.0065 | 34.29 | 1680 | 0.0017 | |
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| 0.0065 | 35.27 | 1728 | 0.0015 | |
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| 0.0065 | 36.24 | 1776 | 0.0017 | |
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| 0.0065 | 37.22 | 1824 | 0.0015 | |
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| 0.0065 | 38.2 | 1872 | 0.0015 | |
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| 0.0065 | 39.18 | 1920 | 0.0014 | |
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| 0.0065 | 40.16 | 1968 | 0.0014 | |
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| 0.0028 | 41.14 | 2016 | 0.0014 | |
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| 0.0028 | 42.12 | 2064 | 0.0026 | |
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| 0.0028 | 43.1 | 2112 | 0.0015 | |
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| 0.0028 | 44.08 | 2160 | 0.0014 | |
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| 0.0028 | 45.06 | 2208 | 0.0013 | |
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| 0.0028 | 46.04 | 2256 | 0.0013 | |
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| 0.0028 | 47.02 | 2304 | 0.0013 | |
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| 0.0028 | 48.0 | 2352 | 0.0013 | |
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| 0.0028 | 48.98 | 2400 | 0.0013 | |
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| 0.0028 | 49.96 | 2448 | 0.0013 | |
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| 0.0028 | 50.94 | 2496 | 0.0013 | |
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| 0.002 | 51.92 | 2544 | 0.0012 | |
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| 0.002 | 52.9 | 2592 | 0.0012 | |
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| 0.002 | 53.88 | 2640 | 0.0012 | |
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| 0.002 | 54.86 | 2688 | 0.0012 | |
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| 0.002 | 55.84 | 2736 | 0.0013 | |
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| 0.002 | 56.82 | 2784 | 0.0012 | |
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| 0.002 | 57.8 | 2832 | 0.0012 | |
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| 0.002 | 58.78 | 2880 | 0.0012 | |
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| 0.002 | 59.76 | 2928 | 0.0012 | |
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| 0.002 | 60.73 | 2976 | 0.0012 | |
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| 0.0016 | 61.71 | 3024 | 0.0012 | |
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| 0.0016 | 62.69 | 3072 | 0.0012 | |
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| 0.0016 | 63.67 | 3120 | 0.0012 | |
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| 0.0016 | 64.65 | 3168 | 0.0012 | |
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| 0.0016 | 65.63 | 3216 | 0.0012 | |
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| 0.0016 | 66.61 | 3264 | 0.0012 | |
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| 0.0016 | 67.59 | 3312 | 0.0012 | |
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| 0.0016 | 68.57 | 3360 | 0.0012 | |
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| 0.0016 | 69.55 | 3408 | 0.0012 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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