transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_F04
  results: []
---

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# torgo_xlsr_finetune_F04

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: 1.4132
- Wer: 0.2275

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4699        | 0.85  | 1000  | 3.2861          | 1.0    |
| 2.1971        | 1.69  | 2000  | 2.0008          | 0.8514 |
| 0.9545        | 2.54  | 3000  | 1.4512          | 0.6358 |
| 0.6665        | 3.39  | 4000  | 1.4047          | 0.5008 |
| 0.5094        | 4.24  | 5000  | 1.3973          | 0.4457 |
| 0.4719        | 5.08  | 6000  | 1.4290          | 0.4066 |
| 0.4183        | 5.93  | 7000  | 1.4807          | 0.3761 |
| 0.3525        | 6.78  | 8000  | 1.5710          | 0.3667 |
| 0.3112        | 7.63  | 9000  | 1.4555          | 0.3268 |
| 0.2876        | 8.47  | 10000 | 1.4537          | 0.2988 |
| 0.2321        | 9.32  | 11000 | 1.6268          | 0.3200 |
| 0.2456        | 10.17 | 12000 | 1.3804          | 0.2852 |
| 0.2376        | 11.02 | 13000 | 1.6112          | 0.3141 |
| 0.2169        | 11.86 | 14000 | 1.4480          | 0.2988 |
| 0.2106        | 12.71 | 15000 | 1.6790          | 0.2929 |
| 0.2055        | 13.56 | 16000 | 1.5383          | 0.2963 |
| 0.1601        | 14.41 | 17000 | 1.4142          | 0.2555 |
| 0.1631        | 15.25 | 18000 | 1.5318          | 0.2470 |
| 0.1481        | 16.1  | 19000 | 1.6078          | 0.2453 |
| 0.1374        | 16.95 | 20000 | 1.3588          | 0.2360 |
| 0.1349        | 17.8  | 21000 | 1.3788          | 0.2309 |
| 0.1284        | 18.64 | 22000 | 1.4818          | 0.2326 |
| 0.1328        | 19.49 | 23000 | 1.4132          | 0.2275 |


### Framework versions

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