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_M01
  results: []
---

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# 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3034
- Wer: 0.2292

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4693        | 0.85  | 1000  | 3.2808          | 1.0    |
| 1.4742        | 1.7   | 2000  | 1.3840          | 0.7581 |
| 0.7802        | 2.55  | 3000  | 1.2332          | 0.5535 |
| 0.5771        | 3.4   | 4000  | 1.3305          | 0.4423 |
| 0.4685        | 4.25  | 5000  | 1.2289          | 0.4032 |
| 0.4235        | 5.1   | 6000  | 1.3615          | 0.3540 |
| 0.3593        | 5.95  | 7000  | 1.1796          | 0.3311 |
| 0.3319        | 6.8   | 8000  | 1.2863          | 0.3336 |
| 0.298         | 7.65  | 9000  | 1.2067          | 0.3022 |
| 0.2729        | 8.5   | 10000 | 1.5681          | 0.3090 |
| 0.24          | 9.35  | 11000 | 1.3628          | 0.3022 |
| 0.2104        | 10.2  | 12000 | 1.6944          | 0.3022 |
| 0.2285        | 11.05 | 13000 | 1.6160          | 0.2997 |
| 0.2027        | 11.89 | 14000 | 1.6614          | 0.3081 |
| 0.2013        | 12.74 | 15000 | 1.3976          | 0.2683 |
| 0.1945        | 13.59 | 16000 | 1.0957          | 0.2317 |
| 0.1644        | 14.44 | 17000 | 1.4140          | 0.2699 |
| 0.163         | 15.29 | 18000 | 1.2615          | 0.2436 |
| 0.1414        | 16.14 | 19000 | 1.4278          | 0.2640 |
| 0.1476        | 16.99 | 20000 | 1.3421          | 0.2360 |
| 0.1415        | 17.84 | 21000 | 1.3527          | 0.2402 |
| 0.1217        | 18.69 | 22000 | 1.3593          | 0.2377 |
| 0.1353        | 19.54 | 23000 | 1.3034          | 0.2292 |


### Framework versions

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