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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_F04
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_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
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