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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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Evaluation results

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