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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E50_speed
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. -->
# wav2vec2-E50_speed
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7201
- Cer: 34.5747
## 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 38.2863 | 0.1289 | 200 | 4.9788 | 100.0 |
| 4.8884 | 0.2579 | 400 | 4.7635 | 100.0 |
| 4.7532 | 0.3868 | 600 | 4.6460 | 100.0 |
| 4.7285 | 0.5158 | 800 | 4.6380 | 100.0 |
| 4.6656 | 0.6447 | 1000 | 4.6877 | 100.0 |
| 4.6484 | 0.7737 | 1200 | 4.6586 | 100.0 |
| 4.6328 | 0.9026 | 1400 | 4.6110 | 100.0 |
| 4.5589 | 1.0316 | 1600 | 4.5007 | 100.0 |
| 4.4938 | 1.1605 | 1800 | 4.4103 | 98.0557 |
| 4.3191 | 1.2895 | 2000 | 4.2620 | 95.5768 |
| 3.9702 | 1.4184 | 2200 | 3.6438 | 68.0099 |
| 3.3814 | 1.5474 | 2400 | 3.1348 | 60.4323 |
| 2.9655 | 1.6763 | 2600 | 2.9093 | 59.5865 |
| 2.7274 | 1.8053 | 2800 | 2.5505 | 51.1396 |
| 2.5117 | 1.9342 | 3000 | 2.2604 | 46.0644 |
| 2.3308 | 2.0632 | 3200 | 2.0918 | 42.4871 |
| 2.1864 | 2.1921 | 3400 | 2.0284 | 41.0832 |
| 2.0692 | 2.3211 | 3600 | 1.9906 | 40.9774 |
| 2.0208 | 2.4500 | 3800 | 1.9112 | 38.6278 |
| 1.9439 | 2.5790 | 4000 | 1.8649 | 38.3870 |
| 1.8928 | 2.7079 | 4200 | 1.7703 | 35.7789 |
| 1.8225 | 2.8369 | 4400 | 1.7312 | 34.8508 |
| 1.8341 | 2.9658 | 4600 | 1.7201 | 34.5747 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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