mms-1b-swagen-balanced-model
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: 0.2287
- Wer: 0.1900
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
16.6036 | 0.2392 | 100 | 4.9362 | 1.0067 |
8.5948 | 0.4785 | 200 | 4.2592 | 1.0 |
7.8678 | 0.7177 | 300 | 3.5876 | 1.0 |
5.2547 | 0.9569 | 400 | 0.3053 | 0.2088 |
0.5538 | 1.1962 | 500 | 0.2696 | 0.2008 |
0.5574 | 1.4354 | 600 | 0.2543 | 0.1941 |
0.5282 | 1.6746 | 700 | 0.2459 | 0.1941 |
0.4837 | 1.9139 | 800 | 0.2387 | 0.1931 |
0.4969 | 2.1531 | 900 | 0.2372 | 0.1996 |
0.5005 | 2.3923 | 1000 | 0.2337 | 0.1941 |
0.4712 | 2.6316 | 1100 | 0.2309 | 0.1921 |
0.4783 | 2.8708 | 1200 | 0.2287 | 0.1902 |
0.4406 | 3.1100 | 1300 | 0.2316 | 0.1916 |
0.463 | 3.3493 | 1400 | 0.2288 | 0.1892 |
0.448 | 3.5885 | 1500 | 0.2317 | 0.1914 |
0.4567 | 3.8278 | 1600 | 0.2293 | 0.1945 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
facebook/mms-1b-all