End of training

README.md

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----
-license: mit
----
+---
+base_model: openai/whisper-small
+datasets:
+- lord-reso/inbrowser-proctor-dataset
+language:
+- en
+library_name: peft
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: Whisper-Small-Inbrowser-Proctor-LORA
+  results: []
+---
+
+<!-- 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-Small-Inbrowser-Proctor-LORA
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Inbrowser Procotor Dataset dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.3714
+- eval_wer: 20.6913
+- eval_runtime: 58.8679
+- eval_samples_per_second: 1.189
+- eval_steps_per_second: 0.153
+- epoch: 9.8214
+- step: 275
+
+## 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: 5e-06
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- PEFT 0.12.1.dev0
+- Transformers 4.45.0.dev0
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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