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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Wav2Vec2_FullDataset
results: []
datasets:
- timit-asr/timit_asr
language:
- en
metrics:
- wer
base_model:
- facebook/wav2vec2-base
pipeline_tag: automatic-speech-recognition
library_name: transformers
---
<!-- 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. -->
# Wav2Vec2_FullDataset
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5144
- Wer: 0.3292
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5171 | 1.0 | 500 | 1.8108 | 1.0014 |
| 0.8397 | 2.01 | 1000 | 0.5559 | 0.5358 |
| 0.431 | 3.01 | 1500 | 0.4265 | 0.4469 |
| 0.2931 | 4.02 | 2000 | 0.4034 | 0.4193 |
| 0.2247 | 5.02 | 2500 | 0.4595 | 0.4076 |
| 0.1855 | 6.02 | 3000 | 0.4543 | 0.3991 |
| 0.1497 | 7.03 | 3500 | 0.4894 | 0.3839 |
| 0.1339 | 8.03 | 4000 | 0.4514 | 0.3836 |
| 0.1166 | 9.04 | 4500 | 0.4432 | 0.3682 |
| 0.1063 | 10.04 | 5000 | 0.4781 | 0.3773 |
| 0.0923 | 11.04 | 5500 | 0.4548 | 0.3699 |
| 0.0899 | 12.05 | 6000 | 0.4836 | 0.3636 |
| 0.0802 | 13.05 | 6500 | 0.5117 | 0.3637 |
| 0.0726 | 14.06 | 7000 | 0.4453 | 0.3653 |
| 0.07 | 15.06 | 7500 | 0.4983 | 0.3581 |
| 0.0641 | 16.06 | 8000 | 0.4922 | 0.3603 |
| 0.0561 | 17.07 | 8500 | 0.4947 | 0.3517 |
| 0.0522 | 18.07 | 9000 | 0.5132 | 0.3513 |
| 0.0483 | 19.08 | 9500 | 0.4815 | 0.3453 |
| 0.0419 | 20.08 | 10000 | 0.5556 | 0.3459 |
| 0.0402 | 21.08 | 10500 | 0.5141 | 0.3428 |
| 0.0368 | 22.09 | 11000 | 0.5176 | 0.3437 |
| 0.0322 | 23.09 | 11500 | 0.5326 | 0.3403 |
| 0.0305 | 24.1 | 12000 | 0.5046 | 0.3366 |
| 0.0258 | 25.1 | 12500 | 0.5219 | 0.3315 |
| 0.0254 | 26.1 | 13000 | 0.5166 | 0.3289 |
| 0.0226 | 27.11 | 13500 | 0.5177 | 0.3311 |
| 0.0226 | 28.11 | 14000 | 0.5187 | 0.3302 |
| 0.0209 | 29.12 | 14500 | 0.5144 | 0.3292 |
### Framework versions
- Transformers 4.17.0
- Pytorch 2.5.1+cu121
- Datasets 1.18.3
- Tokenizers 0.20.3 |