wav2vec2-large-xls-r-300m-en-libri-more-steps
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the librispeech_asr dataset. It achieves the following results on the evaluation set:
- Loss: 1.7624
- Wer: 0.8772
- Cer: 0.3762
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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
No log | 1.94 | 33 | 2.9987 | 1.0 | 1.0 |
No log | 3.88 | 66 | 2.8951 | 1.0 | 1.0 |
No log | 5.82 | 99 | 2.8732 | 1.0 | 1.0 |
3.781 | 7.76 | 132 | 2.6057 | 1.0 | 1.0 |
3.781 | 9.71 | 165 | 1.9015 | 1.0154 | 0.5616 |
3.781 | 11.65 | 198 | 1.5226 | 0.9263 | 0.4462 |
2.2258 | 13.59 | 231 | 1.5116 | 0.8913 | 0.3967 |
2.2258 | 15.53 | 264 | 1.5634 | 0.8922 | 0.3842 |
2.2258 | 17.47 | 297 | 1.7016 | 0.8876 | 0.3796 |
0.7946 | 19.41 | 330 | 1.7624 | 0.8772 | 0.3762 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cpu
- Datasets 1.18.3
- Tokenizers 0.12.1
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