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README.md
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---
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license: apache-2.0
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base_model: openai/whisper-medium
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tags:
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- generated_from_trainer
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model-index:
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- name: MAScIR_elderly_whisper-medium-LoRA-ev
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# MAScIR_elderly_whisper-medium-LoRA-ev
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0213
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 200
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.3194 | 0.19 | 100 | 0.2974 |
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| 0.2485 | 0.37 | 200 | 0.2865 |
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| 0.2532 | 0.56 | 300 | 0.2810 |
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| 0.2306 | 0.74 | 400 | 0.2225 |
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| 0.1954 | 0.93 | 500 | 0.2355 |
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| 0.1178 | 1.11 | 600 | 0.1883 |
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| 0.1087 | 1.3 | 700 | 0.1567 |
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| 0.098 | 1.48 | 800 | 0.1593 |
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| 0.0661 | 1.67 | 900 | 0.0985 |
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| 0.0675 | 1.85 | 1000 | 0.0602 |
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| 0.0297 | 2.04 | 1100 | 0.0543 |
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| 0.0172 | 2.22 | 1200 | 0.0436 |
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| 0.0157 | 2.41 | 1300 | 0.0403 |
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| 0.0143 | 2.59 | 1400 | 0.0317 |
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| 0.0167 | 2.78 | 1500 | 0.0265 |
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| 0.0095 | 2.96 | 1600 | 0.0213 |
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### Framework versions
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- Transformers 4.33.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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