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---
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2809
- Wer: 0.2462
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.7203 | 0.83 | 1000 | 3.5860 | 1.0 |
| 3.3181 | 1.66 | 2000 | 3.2148 | 1.0 |
| 1.547 | 2.49 | 3000 | 1.6683 | 0.8497 |
| 0.8041 | 3.32 | 4000 | 1.1466 | 0.6036 |
| 0.5827 | 4.15 | 5000 | 1.1892 | 0.5093 |
| 0.5022 | 4.98 | 6000 | 1.1251 | 0.4295 |
| 0.4373 | 5.81 | 7000 | 1.4837 | 0.4270 |
| 0.3729 | 6.64 | 8000 | 1.1526 | 0.3430 |
| 0.3448 | 7.47 | 9000 | 1.0968 | 0.3489 |
| 0.2964 | 8.3 | 10000 | 1.2292 | 0.3014 |
| 0.2806 | 9.13 | 11000 | 1.4337 | 0.3345 |
| 0.2684 | 9.96 | 12000 | 1.4606 | 0.3472 |
| 0.2587 | 10.79 | 13000 | 1.1020 | 0.2937 |
| 0.2187 | 11.62 | 14000 | 1.3086 | 0.3192 |
| 0.2052 | 12.45 | 15000 | 1.3270 | 0.2912 |
| 0.1757 | 13.28 | 16000 | 1.2323 | 0.2784 |
| 0.2061 | 14.11 | 17000 | 1.1289 | 0.2716 |
| 0.1749 | 14.94 | 18000 | 1.2851 | 0.2784 |
| 0.1476 | 15.77 | 19000 | 1.1545 | 0.2547 |
| 0.1446 | 16.6 | 20000 | 1.2718 | 0.2487 |
| 0.1319 | 17.43 | 21000 | 1.2026 | 0.2487 |
| 0.1533 | 18.26 | 22000 | 1.2299 | 0.2530 |
| 0.1349 | 19.09 | 23000 | 1.3010 | 0.2513 |
| 0.1185 | 19.92 | 24000 | 1.2809 | 0.2462 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.13.3
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