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---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- QEC
metrics:
- wer
model-index:
- name: whisper-medium-quartr
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Quartr Earnings Calls
type: QEC
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 22.31368880573745
---
<!-- 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-medium-quartr
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Quartr Earnings Calls dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6825
- Wer: 22.3137
## 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: 8.120528078446462e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 84
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5817 | 0.32 | 100 | 0.5708 | 21.9832 |
| 0.5817 | 0.64 | 200 | 0.5332 | 20.1559 |
| 0.5253 | 0.96 | 300 | 0.5127 | 25.4256 |
| 0.3177 | 1.28 | 400 | 0.5276 | 28.5688 |
| 0.3603 | 1.61 | 500 | 0.5195 | 22.2950 |
| 0.3374 | 1.93 | 600 | 0.5101 | 24.3343 |
| 0.1734 | 2.25 | 700 | 0.5530 | 23.1743 |
| 0.2002 | 2.57 | 800 | 0.5525 | 21.1537 |
| 0.1894 | 2.89 | 900 | 0.5589 | 21.7774 |
| 0.0868 | 3.21 | 1000 | 0.6291 | 23.4487 |
| 0.0931 | 3.53 | 1100 | 0.6410 | 21.9208 |
| 0.1094 | 3.85 | 1200 | 0.6339 | 22.5008 |
| 0.1007 | 4.17 | 1300 | 0.6698 | 21.7524 |
| 0.0652 | 4.49 | 1400 | 0.6820 | 22.3262 |
| 0.0614 | 4.82 | 1500 | 0.6825 | 22.3137 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.1.dev0
- Tokenizers 0.15.2
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