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_F01
  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_F01

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: 1.5082
- Wer: 0.2438

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5402        | 0.6   | 1000  | 3.3380          | 1.0    |
| 2.2307        | 1.2   | 2000  | 1.8396          | 0.8959 |
| 1.0275        | 1.79  | 3000  | 1.5920          | 0.6564 |
| 0.7496        | 2.39  | 4000  | 1.6012          | 0.5640 |
| 0.6224        | 2.99  | 5000  | 1.3718          | 0.4902 |
| 0.5017        | 3.59  | 6000  | 1.8025          | 0.4902 |
| 0.4519        | 4.19  | 7000  | 1.4430          | 0.4017 |
| 0.4049        | 4.78  | 8000  | 1.6817          | 0.3748 |
| 0.3936        | 5.38  | 9000  | 1.5499          | 0.4069 |
| 0.384         | 5.98  | 10000 | 1.3839          | 0.3488 |
| 0.3331        | 6.58  | 11000 | 1.4815          | 0.3614 |
| 0.3168        | 7.18  | 12000 | 1.6359          | 0.3636 |
| 0.3262        | 7.78  | 13000 | 1.4287          | 0.3540 |
| 0.2877        | 8.37  | 14000 | 1.3445          | 0.3132 |
| 0.2684        | 8.97  | 15000 | 1.2778          | 0.2911 |
| 0.2306        | 9.57  | 16000 | 1.5658          | 0.3033 |
| 0.2215        | 10.17 | 17000 | 1.6831          | 0.2959 |
| 0.2381        | 10.77 | 18000 | 1.4930          | 0.2798 |
| 0.2237        | 11.36 | 19000 | 1.4210          | 0.2985 |
| 0.2227        | 11.96 | 20000 | 1.5231          | 0.2950 |
| 0.1965        | 12.56 | 21000 | 1.5101          | 0.2777 |
| 0.187         | 13.16 | 22000 | 1.6570          | 0.2998 |
| 0.1974        | 13.76 | 23000 | 1.4534          | 0.2772 |
| 0.1816        | 14.35 | 24000 | 1.6751          | 0.2755 |
| 0.1753        | 14.95 | 25000 | 1.5616          | 0.2707 |
| 0.1634        | 15.55 | 26000 | 1.4873          | 0.2469 |
| 0.1405        | 16.15 | 27000 | 1.6986          | 0.2590 |
| 0.1515        | 16.75 | 28000 | 1.5311          | 0.2477 |
| 0.1532        | 17.34 | 29000 | 1.3262          | 0.2403 |
| 0.1541        | 17.94 | 30000 | 1.3799          | 0.2477 |
| 0.1386        | 18.54 | 31000 | 1.4252          | 0.2408 |
| 0.1389        | 19.14 | 32000 | 1.5260          | 0.2434 |
| 0.1164        | 19.74 | 33000 | 1.5082          | 0.2438 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.13.3
