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---
library_name: transformers
base_model: Harveenchadha/wav2vec2-pretrained-clsril-23-10k
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: indic-nepali-large-large-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. -->
# indic-nepali-large-large-colab
This model is a fine-tuned version of [Harveenchadha/wav2vec2-pretrained-clsril-23-10k](https://huggingface.co/Harveenchadha/wav2vec2-pretrained-clsril-23-10k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7848
- Wer: 1.0
## 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: 5e-05
- 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: 16
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---:|
| 11.7001 | 0.9479 | 400 | 3.9168 | 1.0 |
| 3.8147 | 1.8957 | 800 | 3.8061 | 1.0 |
| 3.7988 | 2.8436 | 1200 | 3.8261 | 1.0 |
| 3.8006 | 3.7915 | 1600 | 3.7865 | 1.0 |
| 3.8082 | 4.7393 | 2000 | 3.8160 | 1.0 |
| 3.7948 | 5.6872 | 2400 | 3.7880 | 1.0 |
| 3.7931 | 6.6351 | 2800 | 3.7908 | 1.0 |
| 3.79 | 7.5829 | 3200 | 3.7990 | 1.0 |
| 3.7937 | 8.5308 | 3600 | 3.7849 | 1.0 |
| 3.7837 | 9.4787 | 4000 | 3.7994 | 1.0 |
| 3.7829 | 10.4265 | 4400 | 3.7841 | 1.0 |
| 3.781 | 11.3744 | 4800 | 3.7927 | 1.0 |
| 3.777 | 12.3223 | 5200 | 3.7849 | 1.0 |
| 3.7819 | 13.2701 | 5600 | 3.7875 | 1.0 |
| 3.7697 | 14.2180 | 6000 | 3.7855 | 1.0 |
| 3.7794 | 15.1659 | 6400 | 3.7848 | 1.0 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.19.1
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