ii

README.md

@@ -3,38 +3,30 @@ language:
 - el
 license: apache-2.0
 tags:
-- whisper-event
+- hf-asr-leaderboard, whisper-medium, mozilla-foundation/common_voice_11_0, greek,
+  whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_11_0,google/fleurs
-metrics:
-- wer
+- mozilla-foundation/common_voice_11_0
 model-index:
-- name: Whisper Medium El Greco
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: mozilla-foundation/common_voice_11_0,google/fleurs
-      type: mozilla-foundation/common_voice_11_0,google/fleurs
-      config: null
-      split: None
-    metrics:
-    - name: Wer
-      type: wer
-      value: 11.199851411589897
+- name: Whisper Medium El Greco Greek
+  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 Medium El Greco
+# Whisper Medium El Greco Greek
 
-This model is a fine-tuned version of [emilios/whisper-medium-el](https://huggingface.co/emilios/whisper-medium-el) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3801
-- Wer: 11.1999
+- eval_loss: 0.3924
+- eval_wer: 12.4443
+- eval_runtime: 1211.1631
+- eval_samples_per_second: 1.4
+- eval_steps_per_second: 0.088
+- epoch: 4.04
+- step: 5000
 
 ## Model description
 
@@ -63,17 +55,6 @@ The following hyperparameters were used during training:
 - training_steps: 5000
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.0176        | 2.49  | 1000 | 0.2945          | 12.6114 |
-| 0.0064        | 4.98  | 2000 | 0.3423          | 12.2307 |
-| 0.0022        | 7.46  | 3000 | 0.3632          | 11.5899 |
-| 0.0014        | 9.95  | 4000 | 0.3788          | 11.2556 |
-| 0.0008        | 12.44 | 5000 | 0.3801          | 11.1999 |
-
-
 ### Framework versions
 
 - Transformers 4.26.0.dev0

README.md.new

@@ -0,0 +1,82 @@
+---
+language:
+- el
+license: apache-2.0
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0,google/fleurs
+metrics:
+- wer
+model-index:
+- name: Whisper Medium El Greco
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: mozilla-foundation/common_voice_11_0,google/fleurs
+      type: mozilla-foundation/common_voice_11_0,google/fleurs
+      config: null
+      split: None
+    metrics:
+    - name: Wer
+      type: wer
+      value: 11.199851411589897
+---
+
+<!-- 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 Medium El Greco
+
+This model is a fine-tuned version of [emilios/whisper-medium-el](https://huggingface.co/emilios/whisper-medium-el) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3801
+- Wer: 11.1999
+
+## 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: 32
+- eval_batch_size: 16
+- 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: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0176        | 2.49  | 1000 | 0.2945          | 12.6114 |
+| 0.0064        | 4.98  | 2000 | 0.3423          | 12.2307 |
+| 0.0022        | 7.46  | 3000 | 0.3632          | 11.5899 |
+| 0.0014        | 9.95  | 4000 | 0.3788          | 11.2556 |
+| 0.0008        | 12.44 | 5000 | 0.3801          | 11.1999 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2