iulik-pisik commited on
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End of training

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README.md ADDED
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+ ---
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+ language:
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+ - ro
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+ license: apache-2.0
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+ base_model: openai/whisper-tiny
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+ tags:
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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ datasets:
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+ - iulik-pisik/horoscop_neti
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Tiny Romanian - Horoscop Neti
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Horoscop Neti
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+ type: iulik-pisik/horoscop_neti
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+ config: default
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+ split: None
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+ args: 'config: ro, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 21.854465806765635
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+ ---
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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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+
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+ # Whisper Tiny Romanian - Horoscop Neti
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Horoscop Neti dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4305
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+ - Wer: 21.8545
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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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: 500
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+ - training_steps: 4000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.0401 | 9.71 | 1000 | 0.3338 | 22.5116 |
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+ | 0.0027 | 19.42 | 2000 | 0.3979 | 22.5359 |
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+ | 0.0013 | 29.13 | 3000 | 0.4230 | 22.0248 |
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+ | 0.001 | 38.83 | 4000 | 0.4305 | 21.8545 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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