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---
language:
- ta
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny Ta - Bharat Ramanathan
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ta
split: test
args: ta
metrics:
- type: wer
value: 30.102694404742998
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ta_in
split: test
metrics:
- type: wer
value: 26.07
name: WER
---
<!-- 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. -->
# Whisper Tiny Ta - Bharat Ramanathan
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3096
- Wer: 30.1027
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.5622 | 0.2 | 1000 | 0.4460 | 41.4141 |
| 0.4151 | 0.4 | 2000 | 0.3657 | 35.1390 |
| 0.3727 | 0.6 | 3000 | 0.3417 | 33.1723 |
| 0.3519 | 0.8 | 4000 | 0.3252 | 31.9497 |
| 0.3354 | 1.0 | 5000 | 0.3192 | 31.3997 |
| 0.3492 | 0.1 | 6000 | 0.3283 | 31.6966 |
| 0.3229 | 0.2 | 7000 | 0.3211 | 31.1339 |
| 0.3193 | 0.3 | 8000 | 0.3138 | 30.5161 |
| 0.314 | 0.4 | 9000 | 0.3112 | 30.1832 |
| 0.3087 | 0.5 | 10000 | 0.3096 | 30.1027 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|