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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: '' |
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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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# |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3350 |
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- Wer: 0.3441 |
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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: 0.0003 |
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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: 8 |
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- total_train_batch_size: 64 |
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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: 400 |
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- num_epochs: 20.0 |
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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 | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 2.2943 | 0.51 | 400 | 4.4367 | 0.9745 | |
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| 2.8816 | 1.02 | 800 | 2.8103 | 1.2576 | |
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| 2.7842 | 1.53 | 1200 | 2.6832 | 1.1330 | |
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| 2.313 | 2.04 | 1600 | 2.6678 | 1.1348 | |
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| 2.2897 | 2.55 | 2000 | 2.5744 | 1.2102 | |
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| 1.3821 | 3.06 | 2400 | 2.9908 | 0.9377 | |
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| 1.074 | 3.57 | 2800 | 2.6649 | 0.8966 | |
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| 1.3643 | 4.08 | 3200 | 1.0064 | 0.7236 | |
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| 0.8286 | 4.59 | 3600 | 0.6339 | 0.5454 | |
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| 0.3872 | 5.1 | 4000 | 0.5170 | 0.4718 | |
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| 0.3654 | 5.61 | 4400 | 0.4386 | 0.4420 | |
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| 0.2672 | 6.12 | 4800 | 0.5186 | 0.4679 | |
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| 0.2519 | 6.63 | 5200 | 0.4238 | 0.4177 | |
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| 0.3293 | 7.14 | 5600 | 0.3584 | 0.3970 | |
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| 0.314 | 7.65 | 6000 | 0.3325 | 0.3911 | |
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| 0.1698 | 8.16 | 6400 | 0.3411 | 0.3855 | |
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| 0.1682 | 8.67 | 6800 | 0.3239 | 0.3801 | |
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| 0.1325 | 9.18 | 7200 | 0.3474 | 0.3832 | |
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| 0.1577 | 9.69 | 7600 | 0.3289 | 0.3839 | |
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| 0.2259 | 10.2 | 8000 | 0.3183 | 0.3756 | |
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| 0.2473 | 10.71 | 8400 | 0.3132 | 0.3654 | |
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| 0.1136 | 11.22 | 8800 | 0.3242 | 0.3670 | |
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| 0.108 | 11.73 | 9200 | 0.3201 | 0.3601 | |
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| 0.0806 | 12.24 | 9600 | 0.3223 | 0.3609 | |
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| 0.0896 | 12.75 | 10000 | 0.3228 | 0.3584 | |
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| 0.1642 | 13.27 | 10400 | 0.3140 | 0.3547 | |
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| 0.1442 | 13.77 | 10800 | 0.3235 | 0.3539 | |
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| 0.0802 | 14.29 | 11200 | 0.3175 | 0.3553 | |
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| 0.0747 | 14.8 | 11600 | 0.3126 | 0.3512 | |
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| 0.0488 | 15.31 | 12000 | 0.3292 | 0.3525 | |
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| 0.0469 | 15.82 | 12400 | 0.3231 | 0.3504 | |
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| 0.1021 | 16.33 | 12800 | 0.3230 | 0.3502 | |
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| 0.0841 | 16.84 | 13200 | 0.3348 | 0.3513 | |
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| 0.0502 | 17.35 | 13600 | 0.3318 | 0.3486 | |
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| 0.059 | 17.86 | 14000 | 0.3359 | 0.3462 | |
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| 0.0417 | 18.37 | 14400 | 0.3310 | 0.3467 | |
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| 0.0322 | 18.88 | 14800 | 0.3325 | 0.3467 | |
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| 0.0531 | 19.39 | 15200 | 0.3357 | 0.3449 | |
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| 0.0623 | 19.9 | 15600 | 0.3350 | 0.3441 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.1 |
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- Tokenizers 0.11.0 |
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