End of training

README.md

@@ -0,0 +1,72 @@
+---
+library_name: peft
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- wft
+- whisper
+- automatic-speech-recognition
+- audio
+- speech
+- generated_from_trainer
+datasets:
+- hf-internal-testing/librispeech_asr_dummy
+model-index:
+- name: wft-test-model
+  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. -->
+
+# wft-test-model
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 1.9885
+- eval_wer: 312.2047
+- eval_cer: 119.2472
+- eval_decode_time: 0.5334
+- eval_wer_time: 0.0169
+- eval_cer_time: 0.0041
+- eval_runtime: 2.8482
+- eval_samples_per_second: 3.511
+- eval_steps_per_second: 0.702
+- epoch: 0.1
+- step: 10
+
+## 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: 0.0005
+- train_batch_size: 4
+- 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: 100
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.45.2
+- Pytorch 2.5.0
+- Datasets 3.0.2
+- Tokenizers 0.20.1