mms-1b-all-bigc-combined-25hrs-52
This model is a fine-tuned version of facebook/mms-1b-all on the BIGC - BEM dataset. It achieves the following results on the evaluation set:
- Loss: 1.3680
- Wer: 0.7224
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 |
---|---|---|---|---|
6.6457 | 0.1300 | 100 | 1.9906 | 0.9112 |
0.8499 | 0.2601 | 200 | 1.4934 | 0.7315 |
0.7669 | 0.3901 | 300 | 1.4285 | 0.7194 |
0.729 | 0.5202 | 400 | 1.3679 | 0.7225 |
0.7028 | 0.6502 | 500 | 1.3397 | 0.7086 |
0.7353 | 0.7802 | 600 | 1.2580 | 0.6957 |
0.7045 | 0.9103 | 700 | 1.3996 | 0.6985 |
0.6958 | 1.0403 | 800 | 1.3539 | 0.6850 |
0.6939 | 1.1704 | 900 | 1.4325 | 0.6892 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
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Base model
facebook/mms-1b-all