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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: tachiwin_totonac
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: ljcamargo--totonac_alpha_1
split: test
args: ljcamargo--totonac_alpha_1
metrics:
- name: Wer
type: wer
value: 0.6465189873417722
---
<!-- 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. -->
# tachiwin_totonac
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7535
- Wer: 0.6465
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 90
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.1063 | 5.19 | 200 | 2.9834 | 1.0 |
| 2.9016 | 10.39 | 400 | 2.4405 | 0.9959 |
| 1.7606 | 15.58 | 600 | 1.1942 | 0.8532 |
| 1.0549 | 20.78 | 800 | 1.1132 | 0.7788 |
| 0.7553 | 25.97 | 1000 | 1.1224 | 0.6899 |
| 0.6639 | 31.51 | 1200 | 1.2641 | 0.7082 |
| 0.5344 | 36.7 | 1400 | 1.3247 | 0.6835 |
| 0.4527 | 41.9 | 1600 | 1.3915 | 0.7022 |
| 0.3839 | 47.09 | 1800 | 1.4051 | 0.6791 |
| 0.3065 | 52.29 | 2000 | 1.3899 | 0.6706 |
| 0.2714 | 57.48 | 2200 | 1.5455 | 0.6573 |
| 0.2437 | 62.68 | 2400 | 1.6798 | 0.6601 |
| 0.2103 | 67.87 | 2600 | 1.7406 | 0.6674 |
| 0.1899 | 73.06 | 2800 | 1.7625 | 0.6522 |
| 0.1841 | 78.26 | 3000 | 1.7443 | 0.6535 |
| 0.1544 | 83.45 | 3200 | 1.7405 | 0.6465 |
| 0.1461 | 88.65 | 3400 | 1.7535 | 0.6465 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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