metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-af-1hr-v2
results: []
wav2vec2-large-xls-r-300m-af-1hr-v2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4465
- Wer: 0.6609
- Cer: 0.2264
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
13.6642 | 2.7778 | 100 | 6.3667 | 1.0 | 1.0 |
4.9297 | 5.5556 | 200 | 3.8947 | 1.0 | 1.0 |
3.3634 | 8.3333 | 300 | 3.0087 | 1.0 | 1.0 |
2.9415 | 11.1111 | 400 | 2.9310 | 1.0 | 1.0 |
2.8979 | 13.8889 | 500 | 2.8946 | 1.0 | 1.0 |
2.8804 | 16.6667 | 600 | 2.8853 | 1.0 | 1.0 |
2.8089 | 19.4444 | 700 | 2.5587 | 1.0 | 0.9801 |
1.5299 | 22.2222 | 800 | 1.3499 | 0.8436 | 0.2927 |
0.6494 | 25.0 | 900 | 1.2093 | 0.6976 | 0.2505 |
0.3557 | 27.7778 | 1000 | 1.2005 | 0.6841 | 0.2389 |
0.249 | 30.5556 | 1100 | 1.2462 | 0.6865 | 0.2371 |
0.1929 | 33.3333 | 1200 | 1.3202 | 0.6744 | 0.2335 |
0.1545 | 36.1111 | 1300 | 1.3346 | 0.6676 | 0.2282 |
0.1352 | 38.8889 | 1400 | 1.4056 | 0.6768 | 0.2361 |
0.1182 | 41.6667 | 1500 | 1.3930 | 0.6635 | 0.2326 |
0.1063 | 44.4444 | 1600 | 1.4446 | 0.6573 | 0.2293 |
0.0972 | 47.2222 | 1700 | 1.3908 | 0.6531 | 0.2273 |
0.0804 | 50.0 | 1800 | 1.4328 | 0.6541 | 0.2262 |
0.0816 | 52.7778 | 1900 | 1.4489 | 0.6586 | 0.2263 |
0.078 | 55.5556 | 2000 | 1.4210 | 0.6581 | 0.2268 |
0.0714 | 58.3333 | 2100 | 1.4393 | 0.6581 | 0.2260 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1