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--- |
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license: apache-2.0 |
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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: torgo_xlsr_finetune_M01 |
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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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# torgo_xlsr_finetune_M01 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8655 |
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- Wer: 0.3060 |
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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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 40 |
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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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| 3.4346 | 0.89 | 1000 | 3.3570 | 1.0 | |
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| 1.3708 | 1.79 | 2000 | 1.5774 | 0.7569 | |
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| 0.7783 | 2.69 | 3000 | 1.6546 | 0.6103 | |
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| 0.5676 | 3.58 | 4000 | 1.3849 | 0.5216 | |
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| 0.4476 | 4.48 | 5000 | 1.5294 | 0.5 | |
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| 0.4264 | 5.37 | 6000 | 1.5832 | 0.4534 | |
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| 0.3434 | 6.27 | 7000 | 1.4397 | 0.4233 | |
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| 0.3371 | 7.16 | 8000 | 1.4635 | 0.4129 | |
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| 0.3268 | 8.06 | 9000 | 1.5989 | 0.3828 | |
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| 0.2623 | 8.95 | 10000 | 1.5145 | 0.3836 | |
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| 0.2755 | 9.85 | 11000 | 1.6695 | 0.3569 | |
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| 0.2304 | 10.74 | 12000 | 1.4313 | 0.3397 | |
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| 0.2052 | 11.64 | 13000 | 1.4242 | 0.3466 | |
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| 0.199 | 12.53 | 14000 | 1.7287 | 0.3405 | |
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| 0.2124 | 13.43 | 15000 | 1.4715 | 0.3086 | |
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| 0.1858 | 14.32 | 16000 | 1.6835 | 0.3086 | |
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| 0.1667 | 15.22 | 17000 | 1.6080 | 0.3233 | |
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| 0.1551 | 16.11 | 18000 | 1.6151 | 0.3293 | |
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| 0.1638 | 17.01 | 19000 | 1.5014 | 0.3034 | |
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| 0.1584 | 17.9 | 20000 | 1.7036 | 0.3233 | |
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| 0.1486 | 18.8 | 21000 | 1.6527 | 0.3207 | |
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| 0.1337 | 19.7 | 22000 | 1.6947 | 0.3181 | |
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| 0.201 | 20.59 | 23000 | 1.9110 | 0.3431 | |
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| 0.2058 | 21.49 | 24000 | 1.6260 | 0.3560 | |
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| 0.1776 | 22.38 | 25000 | 1.8602 | 0.3483 | |
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| 0.1779 | 23.28 | 26000 | 2.0418 | 0.3578 | |
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| 0.1401 | 24.17 | 27000 | 2.0262 | 0.3371 | |
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| 0.1533 | 25.07 | 28000 | 1.7442 | 0.3069 | |
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| 0.1476 | 25.96 | 29000 | 1.7283 | 0.3190 | |
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| 0.1414 | 26.86 | 30000 | 1.7655 | 0.3181 | |
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| 0.1522 | 27.75 | 31000 | 1.6772 | 0.3103 | |
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| 0.146 | 28.65 | 32000 | 1.4420 | 0.3 | |
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| 0.1363 | 29.54 | 33000 | 1.5955 | 0.3276 | |
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| 0.1306 | 30.44 | 34000 | 1.7269 | 0.3336 | |
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| 0.1241 | 31.33 | 35000 | 1.7725 | 0.3216 | |
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| 0.1155 | 32.23 | 36000 | 1.8232 | 0.3086 | |
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| 0.117 | 33.12 | 37000 | 1.8145 | 0.3052 | |
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| 0.0973 | 34.02 | 38000 | 2.0621 | 0.3216 | |
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| 0.1181 | 34.91 | 39000 | 1.6758 | 0.2957 | |
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| 0.1063 | 35.81 | 40000 | 1.6431 | 0.2983 | |
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| 0.094 | 36.71 | 41000 | 1.7967 | 0.3069 | |
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| 0.0937 | 37.6 | 42000 | 1.8469 | 0.3052 | |
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| 0.0931 | 38.5 | 43000 | 1.8364 | 0.3017 | |
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| 0.0897 | 39.39 | 44000 | 1.8655 | 0.3060 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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