---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
model-index:
- name: mms-1b-all-gui
  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-all-gui

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8980
- Cer: 0.2397

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 7.8584        | 0.4329 | 100  | 1.5099          | 0.3558 |
| 2.5647        | 0.8658 | 200  | 1.1562          | 0.3514 |
| 2.3995        | 1.2987 | 300  | 0.8952          | 0.2601 |
| 2.0466        | 1.7316 | 400  | 0.8955          | 0.2396 |
| 1.8489        | 2.1645 | 500  | 0.8439          | 0.2397 |
| 1.6392        | 2.5974 | 600  | 0.8097          | 0.2385 |
| 1.7354        | 3.0303 | 700  | 0.7468          | 0.2136 |
| 1.3546        | 3.4632 | 800  | 0.7213          | 0.2236 |
| 1.3797        | 3.8961 | 900  | 0.7014          | 0.2238 |
| 1.2238        | 4.3290 | 1000 | 0.6774          | 0.1970 |
| 1.2138        | 4.7619 | 1100 | 0.7162          | 0.1940 |
| 1.2993        | 5.1948 | 1200 | 0.8006          | 0.2100 |
| 1.7973        | 5.6277 | 1300 | 1.0200          | 0.2625 |
| 2.4040        | 6.0606 | 1400 | 1.2120          | 0.2859 |
| 2.1873        | 6.4935 | 1500 | 1.0882          | 0.3209 |
| 1.9755        | 6.9264 | 1600 | 1.1028          | 0.4591 |
| 1.8324        | 7.3593 | 1700 | 0.9170          | 0.3022 |
| 1.6503        | 7.7922 | 1800 | 0.8828          | 0.2572 |
| 1.6647        | 8.2251 | 1900 | 0.8677          | 0.2544 |
| 1.6586        | 8.6580 | 2000 | 0.9189          | 0.2337 |
| 1.6733        | 9.0909 | 2100 | 0.8938          | 0.2419 |
| 1.6615        | 9.5238 | 2200 | 0.8966          | 0.2384 |
| 1.6580        | 9.9567 | 2300 | 0.8980          | 0.2397 |


### Framework versions

- Transformers 5.1.0
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2