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libri-alpha-0.5-Temp-1-mse
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 28.9681
- Wer: 0.1160
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
212.5522 | 0.75 | 100 | 55.9161 | 0.1500 |
171.0676 | 1.49 | 200 | 51.5701 | 0.1434 |
159.3247 | 2.24 | 300 | 40.6680 | 0.1416 |
147.7202 | 2.99 | 400 | 36.0320 | 0.1388 |
136.0871 | 3.73 | 500 | 32.8709 | 0.1323 |
126.3071 | 4.48 | 600 | 31.9204 | 0.1298 |
126.9502 | 5.22 | 700 | 31.0903 | 0.1281 |
117.0498 | 5.97 | 800 | 30.5398 | 0.1272 |
117.0928 | 6.72 | 900 | 30.2616 | 0.1262 |
116.35 | 7.46 | 1000 | 30.2445 | 0.1264 |
116.784 | 8.21 | 1100 | 30.0181 | 0.1268 |
111.6779 | 8.96 | 1200 | 29.6434 | 0.1252 |
110.2514 | 9.7 | 1300 | 29.6900 | 0.1233 |
112.603 | 10.45 | 1400 | 29.4023 | 0.1240 |
110.4294 | 11.19 | 1500 | 29.5929 | 0.1239 |
106.3693 | 11.94 | 1600 | 29.4228 | 0.1232 |
102.5095 | 12.69 | 1700 | 29.6106 | 0.1236 |
104.8351 | 13.43 | 1800 | 29.3908 | 0.1220 |
103.6225 | 14.18 | 1900 | 29.5250 | 0.1216 |
102.5769 | 14.93 | 2000 | 29.4744 | 0.1211 |
102.7153 | 15.67 | 2100 | 29.3769 | 0.1203 |
98.3215 | 16.42 | 2200 | 29.3692 | 0.1205 |
100.0971 | 17.16 | 2300 | 29.0029 | 0.1183 |
94.876 | 17.91 | 2400 | 28.9354 | 0.1181 |
100.2511 | 18.66 | 2500 | 28.9513 | 0.1168 |
95.3128 | 19.4 | 2600 | 29.0832 | 0.1166 |
95.2151 | 20.15 | 2700 | 29.0161 | 0.1157 |
92.6844 | 20.9 | 2800 | 29.0543 | 0.1152 |
96.837 | 21.64 | 2900 | 29.2276 | 0.1164 |
94.2866 | 22.39 | 3000 | 28.9697 | 0.1164 |
92.1945 | 23.13 | 3100 | 29.0823 | 0.1169 |
97.7153 | 23.88 | 3200 | 29.0628 | 0.1158 |
95.3836 | 24.63 | 3300 | 28.9681 | 0.1160 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0