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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-tira-colab
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-large-xls-r-300m-tira-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2681
- Wer: 0.2787
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2937 | 1.45 | 400 | 1.0460 | 0.9297 |
| 0.9157 | 2.9 | 800 | 0.5732 | 0.6728 |
| 0.6258 | 4.35 | 1200 | 0.4319 | 0.5434 |
| 0.5114 | 5.8 | 1600 | 0.3822 | 0.5465 |
| 0.4059 | 7.25 | 2000 | 0.3439 | 0.4700 |
| 0.3407 | 8.7 | 2400 | 0.2997 | 0.4778 |
| 0.2938 | 10.14 | 2800 | 0.2956 | 0.4121 |
| 0.2465 | 11.59 | 3200 | 0.2834 | 0.3537 |
| 0.2148 | 13.04 | 3600 | 0.2662 | 0.3779 |
| 0.1711 | 14.49 | 4000 | 0.2724 | 0.3160 |
| 0.1621 | 15.94 | 4400 | 0.2452 | 0.3571 |
| 0.1301 | 17.39 | 4800 | 0.2638 | 0.2927 |
| 0.1119 | 18.84 | 5200 | 0.2724 | 0.2765 |
| 0.1026 | 20.29 | 5600 | 0.2703 | 0.2986 |
| 0.0906 | 21.74 | 6000 | 0.2642 | 0.2638 |
| 0.0785 | 23.19 | 6400 | 0.2653 | 0.2709 |
| 0.0648 | 24.64 | 6800 | 0.2644 | 0.2669 |
| 0.0578 | 26.09 | 7200 | 0.2712 | 0.3123 |
| 0.0514 | 27.54 | 7600 | 0.2703 | 0.2672 |
| 0.0459 | 28.99 | 8000 | 0.2681 | 0.2787 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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