mms-1b-all-swagen-balanced-42
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: 0.2314
- Wer: 0.1916
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: 42
- 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 |
---|---|---|---|---|
7.0483 | 0.4785 | 100 | 3.4104 | 0.9115 |
2.4045 | 0.9569 | 200 | 0.3065 | 0.2120 |
0.2863 | 1.4354 | 300 | 0.2580 | 0.1978 |
0.2588 | 1.9139 | 400 | 0.2474 | 0.1949 |
0.2498 | 2.3923 | 500 | 0.2415 | 0.1965 |
0.2464 | 2.8708 | 600 | 0.2408 | 0.1951 |
0.2474 | 3.3493 | 700 | 0.2406 | 0.1951 |
0.2302 | 3.8278 | 800 | 0.2314 | 0.1916 |
0.2392 | 4.3062 | 900 | 0.2327 | 0.1947 |
0.226 | 4.7847 | 1000 | 0.2311 | 0.1900 |
0.2282 | 5.2632 | 1100 | 0.2305 | 0.1918 |
0.2302 | 5.7416 | 1200 | 0.2315 | 0.1929 |
0.2201 | 6.2201 | 1300 | 0.2283 | 0.1872 |
0.2211 | 6.6986 | 1400 | 0.2253 | 0.1867 |
0.2051 | 7.1770 | 1500 | 0.2279 | 0.1882 |
0.2185 | 7.6555 | 1600 | 0.2287 | 0.1874 |
0.225 | 8.1340 | 1700 | 0.2260 | 0.1892 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
- Downloads last month
- 19
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for csikasote/mms-1b-all-swagen-balanced-42
Base model
facebook/mms-1b-all