---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M02
  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. -->

# torgo_xlsr_finetune_M02

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4526
- Wer: 0.2394

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5091        | 0.85  | 1000  | 3.2824          | 1.0    |
| 1.6986        | 1.7   | 2000  | 1.6782          | 0.7538 |
| 0.8367        | 2.55  | 3000  | 1.1374          | 0.5772 |
| 0.5881        | 3.4   | 4000  | 1.2548          | 0.4567 |
| 0.5024        | 4.26  | 5000  | 1.1946          | 0.3905 |
| 0.4208        | 5.11  | 6000  | 1.3830          | 0.3939 |
| 0.3647        | 5.96  | 7000  | 1.2722          | 0.3404 |
| 0.3357        | 6.81  | 8000  | 1.1639          | 0.3506 |
| 0.2972        | 7.66  | 9000  | 1.3775          | 0.3192 |
| 0.27          | 8.51  | 10000 | 1.2345          | 0.3200 |
| 0.2532        | 9.36  | 11000 | 1.1760          | 0.3158 |
| 0.2171        | 10.21 | 12000 | 1.3310          | 0.2980 |
| 0.2367        | 11.06 | 13000 | 1.2634          | 0.2912 |
| 0.2086        | 11.91 | 14000 | 1.3451          | 0.2742 |
| 0.2023        | 12.77 | 15000 | 1.4799          | 0.2912 |
| 0.1862        | 13.62 | 16000 | 1.7212          | 0.2869 |
| 0.1698        | 14.47 | 17000 | 1.4304          | 0.2725 |
| 0.1489        | 15.32 | 18000 | 1.6233          | 0.2759 |
| 0.1489        | 16.17 | 19000 | 1.6320          | 0.2657 |
| 0.1552        | 17.02 | 20000 | 1.3667          | 0.2377 |
| 0.1414        | 17.87 | 21000 | 1.5199          | 0.2470 |
| 0.1195        | 18.72 | 22000 | 1.4951          | 0.2368 |
| 0.1303        | 19.57 | 23000 | 1.4526          | 0.2394 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.13.3