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whisper-medium-el

Automatic Speech Recognition
Transformers
PyTorch
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Safetensors
Greek
whisper
hf-asr-leaderboard
whisper-medium
mozilla-foundation/common_voice_11_0
greek
whisper-event
Generated from Trainer
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4

Reset to commit 7f6c586

#3
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  1. .ipynb_checkpoints/e3_interleaving-cl-checkpoint.ipynb +0 -0
  2. .ipynb_checkpoints/e5_interleaving-cl-checkpoint.ipynb +0 -0
  3. README.md +19 -17
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  7. pytorch_model.bin +1 -1
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README.md CHANGED
@@ -4,15 +4,9 @@ language:
4
  license: apache-2.0
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  tags:
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  - hf-asr-leaderboard
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- - whisper-medium
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- - mozilla-foundation/common_voice_11_0
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- - greek
10
- - whisper-event
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  - generated_from_trainer
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- - whisper-event
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  datasets:
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  - mozilla-foundation/common_voice_11_0
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- - google/fleurs
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  metrics:
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  - wer
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  model-index:
@@ -22,17 +16,17 @@ model-index:
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  name: Automatic Speech Recognition
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  type: automatic-speech-recognition
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  dataset:
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- name: mozilla-foundation/common_voice_11_0
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  type: mozilla-foundation/common_voice_11_0
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- config: el
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  split: test
 
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  metrics:
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  - name: Wer
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  type: wer
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- value: 10.7448
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  ---
34
 
35
-
36
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
37
  should probably proofread and complete it, then remove this comment. -->
38
 
@@ -40,13 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
40
 
41
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.4245
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- - eval_wer: 10.7448
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- - eval_runtime: 1107.1212
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- - eval_samples_per_second: 1.532
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- - eval_steps_per_second: 0.096
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- - epoch: 33.98
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- - step: 7000
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  ## Model description
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@@ -75,6 +64,19 @@ The following hyperparameters were used during training:
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  - training_steps: 7000
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  - mixed_precision_training: Native AMP
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78
  ### Framework versions
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  - Transformers 4.26.0.dev0
 
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  license: apache-2.0
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  tags:
6
  - hf-asr-leaderboard
 
 
 
 
7
  - generated_from_trainer
 
8
  datasets:
9
  - mozilla-foundation/common_voice_11_0
 
10
  metrics:
11
  - wer
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  model-index:
 
16
  name: Automatic Speech Recognition
17
  type: automatic-speech-recognition
18
  dataset:
19
+ name: Common Voice 11.0
20
  type: mozilla-foundation/common_voice_11_0
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+ config: el
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  split: test
23
+ args: el
24
  metrics:
25
  - name: Wer
26
  type: wer
27
+ value: 10.74479940564636
28
  ---
29
 
 
30
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
31
  should probably proofread and complete it, then remove this comment. -->
32
 
 
34
 
35
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
36
  It achieves the following results on the evaluation set:
37
+ - Loss: 0.4245
38
+ - Wer: 10.7448
 
 
 
 
 
39
 
40
  ## Model description
41
 
 
64
  - training_steps: 7000
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  - mixed_precision_training: Native AMP
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67
+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.0039 | 2.49 | 1000 | 0.3787 | 12.4443 |
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+ | 0.0017 | 4.98 | 2000 | 0.4010 | 12.2864 |
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+ | 0.0006 | 7.46 | 3000 | 0.4108 | 11.6921 |
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+ | 0.0004 | 9.95 | 4000 | 0.4221 | 11.5806 |
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+ | 0.0005 | 12.44 | 5000 | 0.4222 | 11.4134 |
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+ | 0.0006 | 4.03 | 6000 | 0.4230 | 10.9212 |
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+ | 0.0006 | 9.03 | 7000 | 0.4245 | 10.7448 |
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+
79
+
80
  ### Framework versions
81
 
82
  - Transformers 4.26.0.dev0
config.json CHANGED
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  220,
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  50257
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