---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mascir_fr_hubert_version1000
  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. -->

# mascir_fr_hubert_version1000

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co./facebook/hubert-large-ls960-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8026
- Wer: 0.5

## 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: 0.0001
- 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: 1000
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.9386        | 2.0   | 500   | 2.9031          | 0.9856 |
| 2.0513        | 4.0   | 1000  | 1.0727          | 0.9144 |
| 1.0528        | 6.0   | 1500  | 0.7645          | 0.7567 |
| 0.7915        | 8.0   | 2000  | 0.6926          | 0.6744 |
| 0.6418        | 10.0  | 2500  | 0.6881          | 0.6633 |
| 0.5558        | 12.0  | 3000  | 0.6724          | 0.5978 |
| 0.4792        | 14.0  | 3500  | 0.6674          | 0.6011 |
| 0.4236        | 16.0  | 4000  | 0.6907          | 0.5778 |
| 0.3808        | 18.0  | 4500  | 0.7231          | 0.5444 |
| 0.3364        | 20.0  | 5000  | 0.7069          | 0.5456 |
| 0.3193        | 22.0  | 5500  | 0.7189          | 0.5456 |
| 0.2827        | 24.0  | 6000  | 0.7432          | 0.5322 |
| 0.2769        | 26.0  | 6500  | 0.7838          | 0.5656 |
| 0.2543        | 28.0  | 7000  | 0.8012          | 0.5333 |
| 0.2365        | 30.0  | 7500  | 0.8180          | 0.5178 |
| 0.2274        | 32.0  | 8000  | 0.7943          | 0.5233 |
| 0.2095        | 34.0  | 8500  | 0.7664          | 0.5222 |
| 0.2055        | 36.0  | 9000  | 0.7621          | 0.5122 |
| 0.2044        | 38.0  | 9500  | 0.7712          | 0.5056 |
| 0.1946        | 40.0  | 10000 | 0.7987          | 0.4989 |
| 0.1891        | 42.0  | 10500 | 0.7978          | 0.5044 |
| 0.1878        | 44.0  | 11000 | 0.7894          | 0.4967 |
| 0.1742        | 46.0  | 11500 | 0.7964          | 0.4944 |
| 0.1701        | 48.0  | 12000 | 0.7990          | 0.4956 |
| 0.163         | 50.0  | 12500 | 0.8026          | 0.5    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3