End of training

README.md

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+---
+language:
+- ko
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- nicekevin/lgevr_sentence_v2_tmp
+model-index:
+- name: nicekevin/whisper_bs_ft_lgevr2_v3_2
+  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. -->
+
+# nicekevin/whisper_bs_ft_lgevr2_v3_2
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the lgevr_sentence_v2 dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.4283
+- eval_cer: 12.9976
+- eval_runtime: 10.4189
+- eval_samples_per_second: 3.743
+- eval_steps_per_second: 0.48
+- epoch: 25.0
+- step: 500
+
+## 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: 2e-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: 500
+- training_steps: 2000
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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+}

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