File size: 3,083 Bytes
09b2462 8d50746 09b2462 8d50746 09b2462 8d50746 09b2462 89b17c6 09b2462 89b17c6 09b2462 89b17c6 09b2462 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- toigen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-toigen-balanced-model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mms-1b-toigen-balanced-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the TOIGEN - TOI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3234
- Wer: 0.3755
## 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
- num_epochs: 2500.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 14.2297 | 0.8850 | 100 | 3.4836 | 1.0056 |
| 4.1389 | 1.7699 | 200 | 0.5562 | 0.5694 |
| 1.3643 | 2.6549 | 300 | 0.4360 | 0.4958 |
| 1.1715 | 3.5398 | 400 | 0.3980 | 0.4824 |
| 1.1309 | 4.4248 | 500 | 0.3785 | 0.4583 |
| 1.0283 | 5.3097 | 600 | 0.3741 | 0.4477 |
| 1.0148 | 6.1947 | 700 | 0.3669 | 0.4403 |
| 0.9961 | 7.0796 | 800 | 0.3607 | 0.4356 |
| 0.9248 | 7.9646 | 900 | 0.3581 | 0.4236 |
| 0.9482 | 8.8496 | 1000 | 0.3463 | 0.4356 |
| 0.8815 | 9.7345 | 1100 | 0.3488 | 0.4273 |
| 0.8209 | 10.6195 | 1200 | 0.3384 | 0.4 |
| 0.8754 | 11.5044 | 1300 | 0.3459 | 0.4051 |
| 0.8454 | 12.3894 | 1400 | 0.3317 | 0.3884 |
| 0.8164 | 13.2743 | 1500 | 0.3319 | 0.4032 |
| 0.7673 | 14.1593 | 1600 | 0.3311 | 0.3921 |
| 0.7953 | 15.0442 | 1700 | 0.3333 | 0.3944 |
| 0.7527 | 15.9292 | 1800 | 0.3313 | 0.3917 |
| 0.763 | 16.8142 | 1900 | 0.3278 | 0.3931 |
| 0.7319 | 17.6991 | 2000 | 0.3234 | 0.3755 |
| 0.7352 | 18.5841 | 2100 | 0.3248 | 0.3806 |
| 0.7017 | 19.4690 | 2200 | 0.3334 | 0.3852 |
| 0.6902 | 20.3540 | 2300 | 0.3304 | 0.3889 |
| 0.707 | 21.2389 | 2400 | 0.3314 | 0.3856 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|