Update README.md

README.md

@@ -1,65 +1,65 @@
----
-license: apache-2.0
-base_model: openai/whisper-tiny.en
-tags:
-- generated_from_trainer
-metrics:
-- wer
-model-index:
-- name: whisper-tiny-en2
-  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-tiny-en2
-
-This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.9164
-- Wer Ortho: 33.1839
-- Wer: 33.7778
-
-## 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: 1e-05
-- train_batch_size: 8
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: constant_with_warmup
-- lr_scheduler_warmup_steps: 50
-- training_steps: 600
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
-| 0.0008        | 125.0 | 500  | 0.9164          | 33.1839   | 33.7778 |
-
-
-### Framework versions
-
-- Transformers 4.41.1
-- Pytorch 2.2.2+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: openai/whisper-tiny.en
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-en2
+  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-tiny-en2
+
+This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on [hf-internal-testing/librispeech_asr_dummy](https://huggingface.co/datasets/hf-internal-testing/librispeech_asr_dummy).
+It achieves the following results on the evaluation set:
+- Loss: 0.9164
+- Wer Ortho: 33.1839
+- Wer: 33.7778
+
+## Model description
+
+It is fine-tuned version of whisper-tiny model for the audio/video transcription feature in [PersonAI](https://personaiweb.vercel.app)
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 50
+- training_steps: 600
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
+| 0.0008        | 125.0 | 500  | 0.9164          | 33.1839   | 33.7778 |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.2.2+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1