---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M01
  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_M01

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8655
- Wer: 0.3060

## 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: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4346        | 0.89  | 1000  | 3.3570          | 1.0    |
| 1.3708        | 1.79  | 2000  | 1.5774          | 0.7569 |
| 0.7783        | 2.69  | 3000  | 1.6546          | 0.6103 |
| 0.5676        | 3.58  | 4000  | 1.3849          | 0.5216 |
| 0.4476        | 4.48  | 5000  | 1.5294          | 0.5    |
| 0.4264        | 5.37  | 6000  | 1.5832          | 0.4534 |
| 0.3434        | 6.27  | 7000  | 1.4397          | 0.4233 |
| 0.3371        | 7.16  | 8000  | 1.4635          | 0.4129 |
| 0.3268        | 8.06  | 9000  | 1.5989          | 0.3828 |
| 0.2623        | 8.95  | 10000 | 1.5145          | 0.3836 |
| 0.2755        | 9.85  | 11000 | 1.6695          | 0.3569 |
| 0.2304        | 10.74 | 12000 | 1.4313          | 0.3397 |
| 0.2052        | 11.64 | 13000 | 1.4242          | 0.3466 |
| 0.199         | 12.53 | 14000 | 1.7287          | 0.3405 |
| 0.2124        | 13.43 | 15000 | 1.4715          | 0.3086 |
| 0.1858        | 14.32 | 16000 | 1.6835          | 0.3086 |
| 0.1667        | 15.22 | 17000 | 1.6080          | 0.3233 |
| 0.1551        | 16.11 | 18000 | 1.6151          | 0.3293 |
| 0.1638        | 17.01 | 19000 | 1.5014          | 0.3034 |
| 0.1584        | 17.9  | 20000 | 1.7036          | 0.3233 |
| 0.1486        | 18.8  | 21000 | 1.6527          | 0.3207 |
| 0.1337        | 19.7  | 22000 | 1.6947          | 0.3181 |
| 0.201         | 20.59 | 23000 | 1.9110          | 0.3431 |
| 0.2058        | 21.49 | 24000 | 1.6260          | 0.3560 |
| 0.1776        | 22.38 | 25000 | 1.8602          | 0.3483 |
| 0.1779        | 23.28 | 26000 | 2.0418          | 0.3578 |
| 0.1401        | 24.17 | 27000 | 2.0262          | 0.3371 |
| 0.1533        | 25.07 | 28000 | 1.7442          | 0.3069 |
| 0.1476        | 25.96 | 29000 | 1.7283          | 0.3190 |
| 0.1414        | 26.86 | 30000 | 1.7655          | 0.3181 |
| 0.1522        | 27.75 | 31000 | 1.6772          | 0.3103 |
| 0.146         | 28.65 | 32000 | 1.4420          | 0.3    |
| 0.1363        | 29.54 | 33000 | 1.5955          | 0.3276 |
| 0.1306        | 30.44 | 34000 | 1.7269          | 0.3336 |
| 0.1241        | 31.33 | 35000 | 1.7725          | 0.3216 |
| 0.1155        | 32.23 | 36000 | 1.8232          | 0.3086 |
| 0.117         | 33.12 | 37000 | 1.8145          | 0.3052 |
| 0.0973        | 34.02 | 38000 | 2.0621          | 0.3216 |
| 0.1181        | 34.91 | 39000 | 1.6758          | 0.2957 |
| 0.1063        | 35.81 | 40000 | 1.6431          | 0.2983 |
| 0.094         | 36.71 | 41000 | 1.7967          | 0.3069 |
| 0.0937        | 37.6  | 42000 | 1.8469          | 0.3052 |
| 0.0931        | 38.5  | 43000 | 1.8364          | 0.3017 |
| 0.0897        | 39.39 | 44000 | 1.8655          | 0.3060 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3