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---
language:
- as
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: kpriyanshu256/whisper-medium-as-200-32-1e-05-bn
model-index:
- name: openai/whisper-medium-Assamese
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: as
split: test
args: as
metrics:
- type: wer
value: 25.6271431149612
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. -->
# openai/whisper-medium-Assamese
This model is a fine-tuned version of [kpriyanshu256/whisper-medium-as-200-32-1e-05-bn](https://huggingface.co/kpriyanshu256/whisper-medium-as-200-32-1e-05-bn) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2247
- Wer: 25.6271
## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- 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: 40
- training_steps: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0864 | 3.13 | 100 | 0.2247 | 25.6271 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1
|