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--- |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: mms-MGB3 |
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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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# mms-MGB3 |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9382 |
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- Wer: 0.6591 |
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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: 1e-05 |
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- train_batch_size: 14 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 9.7535 | 0.13 | 250 | 8.6735 | 1.0023 | |
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| 3.2385 | 0.27 | 500 | 3.3341 | 1.0003 | |
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| 2.3512 | 0.4 | 750 | 2.0937 | 0.9027 | |
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| 1.4967 | 0.53 | 1000 | 1.3694 | 0.7637 | |
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| 1.3214 | 0.67 | 1250 | 1.2237 | 0.7347 | |
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| 1.2072 | 0.8 | 1500 | 1.1672 | 0.7176 | |
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| 1.1913 | 0.93 | 1750 | 1.1334 | 0.7108 | |
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| 1.1127 | 1.07 | 2000 | 1.1102 | 0.7044 | |
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| 1.1454 | 1.2 | 2250 | 1.0919 | 0.6996 | |
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| 1.1128 | 1.33 | 2500 | 1.0763 | 0.6955 | |
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| 1.086 | 1.47 | 2750 | 1.0629 | 0.6916 | |
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| 1.1285 | 1.6 | 3000 | 1.0503 | 0.6888 | |
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| 1.081 | 1.73 | 3250 | 1.0406 | 0.6886 | |
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| 1.0449 | 1.86 | 3500 | 1.0320 | 0.6857 | |
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| 1.0625 | 2.0 | 3750 | 1.0231 | 0.6849 | |
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| 1.0892 | 2.13 | 4000 | 1.0157 | 0.6824 | |
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| 1.0566 | 2.26 | 4250 | 1.0097 | 0.6795 | |
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| 1.0972 | 2.4 | 4500 | 1.0036 | 0.6747 | |
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| 1.0617 | 2.53 | 4750 | 0.9957 | 0.6744 | |
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| 1.0441 | 2.66 | 5000 | 0.9881 | 0.6756 | |
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| 1.0589 | 2.8 | 5250 | 0.9807 | 0.6718 | |
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| 1.0005 | 2.93 | 5500 | 0.9758 | 0.6713 | |
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| 1.0447 | 3.06 | 5750 | 0.9701 | 0.6694 | |
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| 0.9722 | 3.2 | 6000 | 0.9667 | 0.6664 | |
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| 0.9873 | 3.33 | 6250 | 0.9595 | 0.6675 | |
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| 0.9857 | 3.46 | 6500 | 0.9551 | 0.6633 | |
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| 0.9625 | 3.6 | 6750 | 0.9519 | 0.6633 | |
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| 0.9748 | 3.73 | 7000 | 0.9464 | 0.6607 | |
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| 0.9626 | 3.86 | 7250 | 0.9427 | 0.6617 | |
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| 1.0242 | 4.0 | 7500 | 0.9382 | 0.6591 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.13.3 |
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