xls-r-300m-hindi / README.md
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---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8111
- Wer: 0.5177
## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.9733 | 2.59 | 500 | 5.0697 | 1.0 |
| 3.3839 | 5.18 | 1000 | 3.3518 | 1.0 |
| 2.0596 | 7.77 | 1500 | 1.3992 | 0.7869 |
| 1.6102 | 10.36 | 2000 | 1.0712 | 0.6754 |
| 1.4587 | 12.95 | 2500 | 0.9280 | 0.6361 |
| 1.3667 | 15.54 | 3000 | 0.9281 | 0.6155 |
| 1.3042 | 18.13 | 3500 | 0.9037 | 0.5921 |
| 1.2544 | 20.73 | 4000 | 0.8996 | 0.5824 |
| 1.2274 | 23.32 | 4500 | 0.8934 | 0.5797 |
| 1.1763 | 25.91 | 5000 | 0.8643 | 0.5760 |
| 1.149 | 28.5 | 5500 | 0.8251 | 0.5544 |
| 1.1207 | 31.09 | 6000 | 0.8506 | 0.5527 |
| 1.091 | 33.68 | 6500 | 0.8370 | 0.5366 |
| 1.0613 | 36.27 | 7000 | 0.8345 | 0.5352 |
| 1.0495 | 38.86 | 7500 | 0.8380 | 0.5321 |
| 1.0345 | 41.45 | 8000 | 0.8285 | 0.5269 |
| 1.0297 | 44.04 | 8500 | 0.7836 | 0.5141 |
| 1.027 | 46.63 | 9000 | 0.8120 | 0.5180 |
| 0.9876 | 49.22 | 9500 | 0.8109 | 0.5188 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 1.18.1.dev0
- Tokenizers 0.11.0