metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-1hrs-v1
results: []
mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-1hrs-v1
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:
- Wer: 0.2505
- Cer: 0.0866
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: 5e-05
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Val Wer | Val Cer |
|---|---|---|---|---|
| 16.1327 | 1.0 | 37 | 1.1533 | 2.6305 |
| 14.5509 | 2.0 | 74 | 1.4415 | 1.7715 |
| 11.4505 | 3.0 | 111 | 1.1493 | 0.8650 |
| 7.3358 | 4.0 | 148 | 1.0074 | 0.8544 |
| 4.2752 | 5.0 | 185 | 1.0009 | 0.8517 |
| 3.2479 | 6.0 | 222 | 1.0628 | 0.6094 |
| 2.322 | 7.0 | 259 | 0.7326 | 0.2337 |
| 1.5058 | 8.0 | 296 | 0.4135 | 0.1305 |
| 1.0304 | 9.0 | 333 | 0.3108 | 0.1034 |
| 0.8109 | 10.0 | 370 | 0.2843 | 0.0967 |
| 0.7432 | 11.0 | 407 | 0.2771 | 0.0948 |
| 0.6892 | 12.0 | 444 | 0.2725 | 0.0935 |
| 0.6813 | 13.0 | 481 | 0.2694 | 0.0928 |
| 0.6618 | 14.0 | 518 | 0.2683 | 0.0925 |
| 0.6347 | 15.0 | 555 | 0.2661 | 0.0917 |
| 0.6194 | 16.0 | 592 | 0.2648 | 0.0913 |
| 0.6234 | 17.0 | 629 | 0.2643 | 0.0909 |
| 0.6042 | 18.0 | 666 | 0.2610 | 0.0904 |
| 0.6092 | 19.0 | 703 | 0.2608 | 0.0900 |
| 0.6032 | 20.0 | 740 | 0.2588 | 0.0896 |
| 0.5886 | 21.0 | 777 | 0.2578 | 0.0892 |
| 0.5548 | 22.0 | 814 | 0.2559 | 0.0888 |
| 0.5701 | 23.0 | 851 | 0.2557 | 0.0887 |
| 0.591 | 24.0 | 888 | 0.2556 | 0.0885 |
| 0.5481 | 25.0 | 925 | 0.2545 | 0.0882 |
| 0.5437 | 26.0 | 962 | 0.2541 | 0.0879 |
| 0.537 | 27.0 | 999 | 0.2531 | 0.0877 |
| 0.555 | 28.0 | 1036 | 0.2526 | 0.0875 |
| 0.5391 | 29.0 | 1073 | 0.2518 | 0.0873 |
| 0.531 | 30.0 | 1110 | 0.2523 | 0.0873 |
| 0.5248 | 31.0 | 1147 | 0.2517 | 0.0872 |
| 0.5125 | 32.0 | 1184 | 0.2514 | 0.0871 |
| 0.5133 | 33.0 | 1221 | 0.2513 | 0.0870 |
| 0.4936 | 34.0 | 1258 | 0.2519 | 0.0870 |
| 0.5095 | 35.0 | 1295 | 0.2514 | 0.0868 |
| 0.5121 | 36.0 | 1332 | 0.2509 | 0.0867 |
| 0.4983 | 37.0 | 1369 | 0.2505 | 0.0866 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0