metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-nomimosev-aiish
results: []
xlsr-nomimosev-aiish
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0
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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
4.8467 | 1.2945 | 200 | 2.8108 | 1.0 |
2.6337 | 2.5890 | 400 | 2.0411 | 1.0 |
1.2205 | 3.8835 | 600 | 0.1323 | 0.4010 |
0.3704 | 5.1780 | 800 | 0.0457 | 0.1907 |
0.2019 | 6.4725 | 1000 | 0.0216 | 0.1748 |
0.158 | 7.7670 | 1200 | 0.0050 | 0.1027 |
0.1039 | 9.0615 | 1400 | 0.0018 | 0.0134 |
0.0988 | 10.3560 | 1600 | 0.0116 | 0.0159 |
0.0758 | 11.6505 | 1800 | 0.0061 | 0.0110 |
0.0681 | 12.9450 | 2000 | 0.0068 | 0.0208 |
0.0549 | 14.2395 | 2200 | 0.0022 | 0.0232 |
0.0622 | 15.5340 | 2400 | 0.0005 | 0.0355 |
0.0507 | 16.8285 | 2600 | 0.0018 | 0.0061 |
0.0442 | 18.1230 | 2800 | 0.0005 | 0.0012 |
0.044 | 19.4175 | 3000 | 0.0032 | 0.0037 |
0.0428 | 20.7120 | 3200 | 0.0025 | 0.0098 |
0.04 | 22.0065 | 3400 | 0.0253 | 0.0660 |
0.0385 | 23.3010 | 3600 | 0.0008 | 0.0098 |
0.0333 | 24.5955 | 3800 | 0.0003 | 0.0 |
0.0289 | 25.8900 | 4000 | 0.0002 | 0.0 |
0.0225 | 27.1845 | 4200 | 0.0031 | 0.0587 |
0.0275 | 28.4790 | 4400 | 0.0006 | 0.0220 |
0.0275 | 29.7735 | 4600 | 0.0005 | 0.0086 |
0.0295 | 31.0680 | 4800 | 0.0003 | 0.0073 |
0.0281 | 32.3625 | 5000 | 0.0002 | 0.0061 |
0.0254 | 33.6570 | 5200 | 0.0005 | 0.0269 |
0.0229 | 34.9515 | 5400 | 0.0022 | 0.0330 |
0.0203 | 36.2460 | 5600 | 0.0009 | 0.0147 |
0.0224 | 37.5405 | 5800 | 0.0001 | 0.0 |
0.0176 | 38.8350 | 6000 | 0.0001 | 0.0086 |
0.0204 | 40.1294 | 6200 | 0.0004 | 0.0073 |
0.0172 | 41.4239 | 6400 | 0.0004 | 0.0037 |
0.0157 | 42.7184 | 6600 | 0.0001 | 0.0 |
0.0157 | 44.0129 | 6800 | 0.0001 | 0.0 |
0.0146 | 45.3074 | 7000 | 0.0001 | 0.0012 |
0.0105 | 46.6019 | 7200 | 0.0001 | 0.0012 |
0.0122 | 47.8964 | 7400 | 0.0001 | 0.0 |
0.014 | 49.1909 | 7600 | 0.0004 | 0.0012 |
0.0187 | 50.4854 | 7800 | 0.0001 | 0.0024 |
0.0105 | 51.7799 | 8000 | 0.0004 | 0.0024 |
0.0094 | 53.0744 | 8200 | 0.0059 | 0.0037 |
0.0082 | 54.3689 | 8400 | 0.0000 | 0.0 |
0.0106 | 55.6634 | 8600 | 0.0077 | 0.0159 |
0.0082 | 56.9579 | 8800 | 0.0000 | 0.0049 |
0.0085 | 58.2524 | 9000 | 0.0000 | 0.0134 |
0.0054 | 59.5469 | 9200 | 0.0000 | 0.0049 |
0.0077 | 60.8414 | 9400 | 0.0000 | 0.0122 |
0.0098 | 62.1359 | 9600 | 0.0000 | 0.0061 |
0.0094 | 63.4304 | 9800 | 0.0000 | 0.0049 |
0.0069 | 64.7249 | 10000 | 0.0001 | 0.0012 |
0.0081 | 66.0194 | 10200 | 0.0000 | 0.0 |
0.006 | 67.3139 | 10400 | 0.0001 | 0.0 |
0.0061 | 68.6084 | 10600 | 0.0004 | 0.0024 |
0.005 | 69.9029 | 10800 | 0.0000 | 0.0 |
0.0055 | 71.1974 | 11000 | 0.0010 | 0.0037 |
0.0053 | 72.4919 | 11200 | 0.0001 | 0.0012 |
0.0057 | 73.7864 | 11400 | 0.0000 | 0.0061 |
0.0064 | 75.0809 | 11600 | 0.0001 | 0.0012 |
0.0068 | 76.3754 | 11800 | 0.0000 | 0.0012 |
0.0055 | 77.6699 | 12000 | 0.0019 | 0.0134 |
0.0068 | 78.9644 | 12200 | 0.0008 | 0.0073 |
0.0045 | 80.2589 | 12400 | 0.0000 | 0.0061 |
0.0032 | 81.5534 | 12600 | 0.0000 | 0.0073 |
0.0038 | 82.8479 | 12800 | 0.0000 | 0.0 |
0.0028 | 84.1424 | 13000 | 0.0000 | 0.0037 |
0.004 | 85.4369 | 13200 | 0.0000 | 0.0 |
0.0027 | 86.7314 | 13400 | 0.0000 | 0.0 |
0.0019 | 88.0259 | 13600 | 0.0000 | 0.0 |
0.0019 | 89.3204 | 13800 | 0.0000 | 0.0 |
0.0019 | 90.6149 | 14000 | 0.0000 | 0.0 |
0.0016 | 91.9094 | 14200 | 0.0000 | 0.0 |
0.0016 | 93.2039 | 14400 | 0.0000 | 0.0012 |
0.0015 | 94.4984 | 14600 | 0.0000 | 0.0 |
0.0013 | 95.7929 | 14800 | 0.0000 | 0.0 |
0.0023 | 97.0874 | 15000 | 0.0000 | 0.0 |
0.0017 | 98.3819 | 15200 | 0.0000 | 0.0 |
0.0018 | 99.6764 | 15400 | 0.0000 | 0.0 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1