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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_speach_model
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. -->
# my_awesome_speach_model
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: 0.8215
- Accuracy: 0.6154
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.8889 | 6 | 0.6905 | 0.6923 |
| 0.6936 | 1.9259 | 13 | 0.7083 | 0.3077 |
| 0.6859 | 2.9630 | 20 | 0.7061 | 0.3846 |
| 0.6859 | 4.0 | 27 | 0.7065 | 0.4615 |
| 0.6738 | 4.8889 | 33 | 0.7058 | 0.5385 |
| 0.6487 | 5.9259 | 40 | 0.7190 | 0.5385 |
| 0.6487 | 6.9630 | 47 | 0.6488 | 0.6154 |
| 0.5804 | 8.0 | 54 | 0.6696 | 0.6154 |
| 0.6227 | 8.8889 | 60 | 0.7988 | 0.3846 |
| 0.6227 | 9.9259 | 67 | 0.6253 | 0.6923 |
| 0.6318 | 10.9630 | 74 | 0.6760 | 0.6154 |
| 0.6617 | 12.0 | 81 | 0.9642 | 0.3077 |
| 0.6617 | 12.8889 | 87 | 0.7761 | 0.5385 |
| 0.6052 | 13.9259 | 94 | 0.8490 | 0.4615 |
| 0.5238 | 14.9630 | 101 | 0.7963 | 0.4615 |
| 0.5238 | 16.0 | 108 | 0.7485 | 0.5385 |
| 0.452 | 16.8889 | 114 | 0.7720 | 0.5385 |
| 0.3813 | 17.9259 | 121 | 0.7478 | 0.6154 |
| 0.3813 | 18.9630 | 128 | 0.8406 | 0.6154 |
| 0.4809 | 20.0 | 135 | 0.6624 | 0.6923 |
| 0.3698 | 20.8889 | 141 | 0.7520 | 0.6154 |
| 0.3698 | 21.9259 | 148 | 0.8275 | 0.5385 |
| 0.2959 | 22.9630 | 155 | 0.8472 | 0.5385 |
| 0.3976 | 24.0 | 162 | 1.0899 | 0.4615 |
| 0.3976 | 24.8889 | 168 | 0.8758 | 0.5385 |
| 0.3788 | 25.9259 | 175 | 0.5872 | 0.7692 |
| 0.3511 | 26.9630 | 182 | 0.7996 | 0.6154 |
| 0.3511 | 28.0 | 189 | 0.7726 | 0.6154 |
| 0.2797 | 28.8889 | 195 | 0.7310 | 0.6923 |
| 0.2445 | 29.9259 | 202 | 0.7223 | 0.6154 |
| 0.2445 | 30.9630 | 209 | 0.7139 | 0.6923 |
| 0.2299 | 32.0 | 216 | 0.7540 | 0.6923 |
| 0.2101 | 32.8889 | 222 | 0.7878 | 0.6154 |
| 0.2101 | 33.9259 | 229 | 0.7942 | 0.6154 |
| 0.2043 | 34.9630 | 236 | 0.8193 | 0.6154 |
| 0.1638 | 35.5556 | 240 | 0.8215 | 0.6154 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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