mms-1b-all-swagen-balanced-52
This model is a fine-tuned version of facebook/mms-1b-all on the SWAGEN - SWA dataset. It achieves the following results on the evaluation set:
- Loss: 0.2363
- Wer: 0.1912
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 52
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
7.3456 | 0.4785 | 100 | 0.6715 | 0.3445 |
0.3195 | 0.9569 | 200 | 0.2489 | 0.1965 |
0.2575 | 1.4354 | 300 | 0.2368 | 0.1921 |
0.258 | 1.9139 | 400 | 0.2363 | 0.1916 |
0.2338 | 2.3923 | 500 | 0.2295 | 0.1894 |
0.2341 | 2.8708 | 600 | 0.2278 | 0.1896 |
0.2242 | 3.3493 | 700 | 0.2267 | 0.1921 |
0.2266 | 3.8278 | 800 | 0.2285 | 0.1931 |
0.228 | 4.3062 | 900 | 0.2262 | 0.1886 |
0.2282 | 4.7847 | 1000 | 0.2239 | 0.1876 |
0.2162 | 5.2632 | 1100 | 0.2281 | 0.1951 |
0.2206 | 5.7416 | 1200 | 0.2271 | 0.1920 |
0.2182 | 6.2201 | 1300 | 0.2227 | 0.1882 |
0.2174 | 6.6986 | 1400 | 0.2235 | 0.1876 |
0.2014 | 7.1770 | 1500 | 0.2233 | 0.1910 |
0.221 | 7.6555 | 1600 | 0.2248 | 0.1855 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
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facebook/mms-1b-all