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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- bigcgen
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bigcgen-female-5hrs-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. -->
# xls-r-1b-bigcgen-female-5hrs-model
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the BIGCGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7473
- Wer: 0.7080
## 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: 2
- total_train_batch_size: 8
- 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_steps: 500
- num_epochs: 30.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.4237 | 100 | 3.7316 | 1.0 |
| No log | 0.8475 | 200 | 2.8335 | 1.0 |
| No log | 1.2712 | 300 | 2.0310 | 1.0 |
| No log | 1.6949 | 400 | 1.1695 | 0.9975 |
| 5.5638 | 2.1186 | 500 | 1.1579 | 0.9917 |
| 5.5638 | 2.5424 | 600 | 1.1173 | 0.9931 |
| 5.5638 | 2.9661 | 700 | 0.9185 | 0.7612 |
| 5.5638 | 3.3898 | 800 | 0.8461 | 0.8634 |
| 5.5638 | 3.8136 | 900 | 0.7551 | 0.7391 |
| 1.2967 | 4.2373 | 1000 | 0.8461 | 0.8179 |
| 1.2967 | 4.6610 | 1100 | 1.0126 | 0.9311 |
| 1.2967 | 5.0847 | 1200 | 0.7473 | 0.7077 |
| 1.2967 | 5.5085 | 1300 | 0.7741 | 0.7567 |
| 1.2967 | 5.9322 | 1400 | 0.8527 | 0.7521 |
| 0.8911 | 6.3559 | 1500 | 0.9529 | 0.8052 |
| 0.8911 | 6.7797 | 1600 | 1.0235 | 0.8309 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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