---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bem-female-sv
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cicasote/huggingface/runs/tuxgh6td)
# mms-1b-bem-female-sv

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: 0.2132
- Wer: 0.3557

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.3992 | 200  | 0.3566          | 0.5019 |
| No log        | 0.7984 | 400  | 0.2620          | 0.4029 |
| 1.7214        | 1.1976 | 600  | 0.2546          | 0.4100 |
| 1.7214        | 1.5968 | 800  | 0.2359          | 0.3965 |
| 0.2801        | 1.9960 | 1000 | 0.2322          | 0.3810 |
| 0.2801        | 2.3952 | 1200 | 0.2305          | 0.3746 |
| 0.2801        | 2.7944 | 1400 | 0.2258          | 0.3336 |
| 0.2528        | 3.1936 | 1600 | 0.2262          | 0.4309 |
| 0.2528        | 3.5928 | 1800 | 0.2164          | 0.3514 |
| 0.2351        | 3.9920 | 2000 | 0.2215          | 0.3894 |
| 0.2351        | 4.3912 | 2200 | 0.2165          | 0.3624 |
| 0.2351        | 4.7904 | 2400 | 0.2132          | 0.3557 |


### Framework versions

- Transformers 4.43.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1