---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M05
  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_M05

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: 1.2781
- Wer: 0.2436

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5164        | 0.84  | 1000  | 3.3225          | 1.0    |
| 1.535         | 1.68  | 2000  | 1.5429          | 0.7317 |
| 0.8257        | 2.53  | 3000  | 1.3691          | 0.5730 |
| 0.6012        | 3.37  | 4000  | 1.2522          | 0.4660 |
| 0.491         | 4.21  | 5000  | 1.1413          | 0.4295 |
| 0.4401        | 5.05  | 6000  | 1.4117          | 0.3744 |
| 0.3768        | 5.89  | 7000  | 1.3632          | 0.3531 |
| 0.3746        | 6.73  | 8000  | 1.4208          | 0.3557 |
| 0.3127        | 7.58  | 9000  | 1.3584          | 0.3336 |
| 0.2595        | 8.42  | 10000 | 0.9971          | 0.2878 |
| 0.2458        | 9.26  | 11000 | 1.2794          | 0.3166 |
| 0.2638        | 10.1  | 12000 | 1.1851          | 0.2861 |
| 0.2384        | 10.94 | 13000 | 1.2144          | 0.2810 |
| 0.215         | 11.78 | 14000 | 1.1125          | 0.2623 |
| 0.2095        | 12.63 | 15000 | 1.5495          | 0.3081 |
| 0.1939        | 13.47 | 16000 | 1.4090          | 0.2818 |
| 0.1757        | 14.31 | 17000 | 1.3261          | 0.2564 |
| 0.1629        | 15.15 | 18000 | 1.3435          | 0.2453 |
| 0.152         | 15.99 | 19000 | 1.3273          | 0.2479 |
| 0.1516        | 16.84 | 20000 | 1.2215          | 0.2292 |
| 0.155         | 17.68 | 21000 | 1.3536          | 0.2453 |
| 0.135         | 18.52 | 22000 | 1.3292          | 0.2470 |
| 0.1206        | 19.36 | 23000 | 1.2781          | 0.2436 |


### Framework versions

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