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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-MGB3
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-MGB3
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5770
- Wer: 99.9986
## 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: 1e-05
- train_batch_size: 14
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 8.1649 | 0.83 | 250 | 8.8182 | 100.0211 |
| 4.4764 | 1.66 | 500 | 5.1784 | 100.0254 |
| 3.962 | 2.48 | 750 | 4.6853 | 100.0310 |
| 3.7546 | 3.31 | 1000 | 4.4820 | 101.1220 |
| 3.5712 | 4.14 | 1250 | 4.3419 | 101.5181 |
| 5.9242 | 4.97 | 1500 | 4.2276 | 100.0 |
| 6.072 | 5.79 | 1750 | 4.1441 | 100.0 |
| 3.3164 | 6.62 | 2000 | 4.0701 | 100.0 |
| 3.2964 | 7.45 | 2250 | 3.9941 | 100.0 |
| 3.2501 | 8.28 | 2500 | 3.9978 | 100.0 |
| 3.2477 | 9.11 | 2750 | 3.9468 | 100.0 |
| 3.9197 | 9.93 | 3000 | 3.9109 | 100.0 |
| 3.1928 | 10.76 | 3250 | 3.8802 | 100.0 |
| 3.182 | 11.59 | 3500 | 3.8802 | 100.0 |
| 3.181 | 12.42 | 3750 | 3.7959 | 100.0 |
| 4.3975 | 13.25 | 4000 | 3.8292 | 100.0 |
| 3.8885 | 14.07 | 4250 | 3.7765 | 100.0 |
| 4.2643 | 14.9 | 4500 | 3.7765 | 100.0 |
| 3.1381 | 15.73 | 4750 | 3.7338 | 100.0 |
| 3.1197 | 16.56 | 5000 | 3.7391 | 100.0 |
| 3.1345 | 17.38 | 5250 | 3.7267 | 100.0 |
| 4.4275 | 18.21 | 5500 | 3.7405 | 100.0 |
| 4.3669 | 19.04 | 5750 | 3.7220 | 100.0 |
| 3.1225 | 19.87 | 6000 | 3.7093 | 99.9915 |
| 3.8043 | 20.7 | 6250 | 3.6449 | 99.9958 |
| 3.8089 | 21.52 | 6500 | 3.6988 | 100.0 |
| 4.2457 | 22.35 | 6750 | 3.6125 | 100.0 |
| 3.0956 | 23.18 | 7000 | 3.6309 | 99.9972 |
| 3.1013 | 24.01 | 7250 | 3.5845 | 99.9930 |
| 5.8493 | 24.83 | 7500 | 3.5770 | 99.9986 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.13.3
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