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library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: csml_word2vec
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: None
args: default
metrics:
- name: Wer
type: wer
value: 0.12267657992565056
---
<!-- 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. -->
# csml_word2vec
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2183
- Wer: 0.1227
## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.2282 | 1.0 | 100 | 3.1130 | 1.0 |
| 2.9562 | 2.0 | 200 | 2.9543 | 1.0 |
| 2.9212 | 3.0 | 300 | 2.9317 | 1.0 |
| 2.9119 | 4.0 | 400 | 2.9110 | 1.0 |
| 2.9099 | 5.0 | 500 | 2.9099 | 1.0 |
| 2.9027 | 6.0 | 600 | 2.9106 | 1.0 |
| 2.4303 | 7.0 | 700 | 1.9136 | 0.9615 |
| 0.7427 | 8.0 | 800 | 0.5675 | 0.4321 |
| 0.4794 | 9.0 | 900 | 0.4161 | 0.3183 |
| 0.3372 | 10.0 | 1000 | 0.3228 | 0.2441 |
| 0.2685 | 11.0 | 1100 | 0.2762 | 0.1916 |
| 0.2092 | 12.0 | 1200 | 0.2522 | 0.1654 |
| 0.1848 | 13.0 | 1300 | 0.2361 | 0.1564 |
| 0.1678 | 14.0 | 1400 | 0.2246 | 0.1383 |
| 0.1377 | 15.0 | 1500 | 0.2183 | 0.1337 |
| 0.122 | 16.0 | 1600 | 0.2206 | 0.1310 |
| 0.1125 | 17.0 | 1700 | 0.2205 | 0.1285 |
| 0.0938 | 18.0 | 1800 | 0.2219 | 0.1273 |
| 0.0994 | 19.0 | 1900 | 0.2209 | 0.1239 |
| 0.1 | 20.0 | 2000 | 0.2183 | 0.1227 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
|