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This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2965
- Wer: 0.3144
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.888 | 0.51 | 400 | 3.7320 | 0.9440 |
3.1636 | 1.02 | 800 | 2.9188 | 1.1916 |
2.773 | 1.53 | 1200 | 2.3347 | 1.0134 |
0.7198 | 2.04 | 1600 | 0.6678 | 0.4826 |
0.5255 | 2.55 | 2000 | 0.4605 | 0.4135 |
0.3961 | 3.06 | 2400 | 0.4266 | 0.3955 |
0.3424 | 3.57 | 2800 | 0.3786 | 0.3741 |
0.3858 | 4.08 | 3200 | 0.3161 | 0.3552 |
0.3218 | 4.59 | 3600 | 0.3029 | 0.3510 |
0.199 | 5.1 | 4000 | 0.2988 | 0.3418 |
0.2054 | 5.61 | 4400 | 0.2873 | 0.3434 |
0.1704 | 6.12 | 4800 | 0.3129 | 0.3432 |
0.1805 | 6.63 | 5200 | 0.2963 | 0.3413 |
0.2091 | 7.14 | 5600 | 0.2755 | 0.3329 |
0.1971 | 7.65 | 6000 | 0.2706 | 0.3309 |
0.1237 | 8.16 | 6400 | 0.2823 | 0.3270 |
0.123 | 8.67 | 6800 | 0.2754 | 0.3246 |
0.103 | 9.18 | 7200 | 0.2917 | 0.3272 |
0.1143 | 9.69 | 7600 | 0.2885 | 0.3305 |
0.156 | 10.2 | 8000 | 0.2810 | 0.3288 |
0.167 | 10.71 | 8400 | 0.2689 | 0.3232 |
0.0815 | 11.22 | 8800 | 0.2899 | 0.3236 |
0.0844 | 11.73 | 9200 | 0.2798 | 0.3225 |
0.0775 | 12.24 | 9600 | 0.2894 | 0.3224 |
0.0677 | 12.75 | 10000 | 0.2838 | 0.3204 |
0.1383 | 13.27 | 10400 | 0.2959 | 0.3211 |
0.1233 | 13.77 | 10800 | 0.2922 | 0.3213 |
0.0688 | 14.29 | 11200 | 0.2903 | 0.3209 |
0.0655 | 14.8 | 11600 | 0.2868 | 0.3182 |
0.0449 | 15.31 | 12000 | 0.2959 | 0.3172 |
0.0421 | 15.82 | 12400 | 0.2966 | 0.3180 |
0.0858 | 16.33 | 12800 | 0.2941 | 0.3164 |
0.0859 | 16.84 | 13200 | 0.2980 | 0.3165 |
0.0561 | 17.35 | 13600 | 0.2965 | 0.3165 |
0.0506 | 17.86 | 14000 | 0.2935 | 0.3148 |
0.0312 | 18.37 | 14400 | 0.2964 | 0.3154 |
0.0403 | 18.88 | 14800 | 0.2967 | 0.3160 |
0.0924 | 19.39 | 15200 | 0.2955 | 0.3147 |
0.0585 | 19.9 | 15600 | 0.2965 | 0.3144 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.18.1
- Tokenizers 0.11.0
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