End of training

README.md

@@ -1,199 +1,174 @@
 ---
 library_name: transformers
-tags: []
+language:
+- nl
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper Large V2
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
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-## Uses
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-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
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-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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-### Recommendations
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-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
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-## Training Details
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-### Training Data
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-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-### Training Procedure
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-
-#### Preprocessing [optional]
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-[More Information Needed]
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-
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
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-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-[More Information Needed]
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-## Evaluation
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-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
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-#### Testing Data
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-[More Information Needed]
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
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-### Results
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-#### Summary
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-
-## Model Examination [optional]
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-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
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-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
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-### Compute Infrastructure
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+<!-- 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 Large V2
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3489
+- Wer: 17.3755
+
+## 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: 3e-05
+- train_batch_size: 12
+- 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: 20
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.7517        | 0.0449 | 15   | 0.5024          | 40.5912 |
+| 0.4299        | 0.0898 | 30   | 0.3868          | 34.1310 |
+| 0.363         | 0.1347 | 45   | 0.3704          | 25.2001 |
+| 0.3744        | 0.1796 | 60   | 0.3537          | 22.5218 |
+| 0.3731        | 0.2246 | 75   | 0.3554          | 24.5736 |
+| 0.3743        | 0.2695 | 90   | 0.3388          | 22.7566 |
+| 0.3001        | 0.3144 | 105  | 0.3401          | 22.3597 |
+| 0.3382        | 0.3593 | 120  | 0.3262          | 33.1556 |
+| 0.3353        | 0.4042 | 135  | 0.3266          | 28.0469 |
+| 0.325         | 0.4491 | 150  | 0.3247          | 26.7473 |
+| 0.3303        | 0.4940 | 165  | 0.3147          | 22.8616 |
+| 0.2925        | 0.5389 | 180  | 0.3147          | 21.2041 |
+| 0.3109        | 0.5838 | 195  | 0.3108          | 23.1859 |
+| 0.2989        | 0.6287 | 210  | 0.3084          | 24.3570 |
+| 0.3111        | 0.6737 | 225  | 0.3018          | 18.4117 |
+| 0.2918        | 0.7186 | 240  | 0.3033          | 17.6076 |
+| 0.3099        | 0.7635 | 255  | 0.2971          | 21.7151 |
+| 0.2997        | 0.8084 | 270  | 0.2987          | 21.5361 |
+| 0.2898        | 0.8533 | 285  | 0.2923          | 21.5828 |
+| 0.2848        | 0.8982 | 300  | 0.2914          | 17.6452 |
+| 0.285         | 0.9431 | 315  | 0.2874          | 17.7425 |
+| 0.2624        | 0.9880 | 330  | 0.2861          | 16.8489 |
+| 0.169         | 1.0329 | 345  | 0.2948          | 18.5687 |
+| 0.1515        | 1.0778 | 360  | 0.2927          | 26.6540 |
+| 0.1504        | 1.1228 | 375  | 0.2918          | 18.9422 |
+| 0.1484        | 1.1677 | 390  | 0.2916          | 18.3482 |
+| 0.1358        | 1.2126 | 405  | 0.2904          | 17.2198 |
+| 0.128         | 1.2575 | 420  | 0.2895          | 17.6764 |
+| 0.1417        | 1.3024 | 435  | 0.2895          | 23.2572 |
+| 0.1561        | 1.3473 | 450  | 0.2876          | 17.7775 |
+| 0.1445        | 1.3922 | 465  | 0.2874          | 17.5415 |
+| 0.1384        | 1.4371 | 480  | 0.2825          | 16.1420 |
+| 0.1488        | 1.4820 | 495  | 0.2857          | 17.3832 |
+| 0.1701        | 1.5269 | 510  | 0.2779          | 22.6826 |
+| 0.1475        | 1.5719 | 525  | 0.2857          | 25.9860 |
+| 0.144         | 1.6168 | 540  | 0.2790          | 16.3145 |
+| 0.1402        | 1.6617 | 555  | 0.2874          | 21.3948 |
+| 0.1575        | 1.7066 | 570  | 0.2756          | 15.9786 |
+| 0.1409        | 1.7515 | 585  | 0.2815          | 17.0862 |
+| 0.1388        | 1.7964 | 600  | 0.2792          | 18.9176 |
+| 0.1273        | 1.8413 | 615  | 0.2803          | 23.6165 |
+| 0.1537        | 1.8862 | 630  | 0.2758          | 17.5454 |
+| 0.1537        | 1.9311 | 645  | 0.2764          | 15.8373 |
+| 0.1474        | 1.9760 | 660  | 0.2708          | 16.4935 |
+| 0.1111        | 2.0210 | 675  | 0.2805          | 19.4337 |
+| 0.0745        | 2.0659 | 690  | 0.2924          | 18.5388 |
+| 0.0639        | 2.1108 | 705  | 0.2917          | 15.8269 |
+| 0.0673        | 2.1557 | 720  | 0.2945          | 16.9306 |
+| 0.066         | 2.2006 | 735  | 0.2955          | 16.3677 |
+| 0.0714        | 2.2455 | 750  | 0.2933          | 16.2289 |
+| 0.0701        | 2.2904 | 765  | 0.2911          | 20.4558 |
+| 0.0631        | 2.3353 | 780  | 0.2971          | 17.1316 |
+| 0.064         | 2.3802 | 795  | 0.2916          | 15.3846 |
+| 0.0659        | 2.4251 | 810  | 0.2971          | 15.1602 |
+| 0.0615        | 2.4701 | 825  | 0.2878          | 20.4480 |
+| 0.0723        | 2.5150 | 840  | 0.2935          | 14.7569 |
+| 0.0695        | 2.5599 | 855  | 0.2846          | 15.6570 |
+| 0.0704        | 2.6048 | 870  | 0.2919          | 19.4000 |
+| 0.0642        | 2.6497 | 885  | 0.2849          | 17.7373 |
+| 0.0684        | 2.6946 | 900  | 0.2888          | 15.9164 |
+| 0.077         | 2.7395 | 915  | 0.2828          | 15.5052 |
+| 0.0708        | 2.7844 | 930  | 0.2858          | 17.0538 |
+| 0.065         | 2.8293 | 945  | 0.2829          | 20.8617 |
+| 0.0788        | 2.8743 | 960  | 0.2854          | 19.5621 |
+| 0.0677        | 2.9192 | 975  | 0.2825          | 16.6984 |
+| 0.0642        | 2.9641 | 990  | 0.2887          | 16.1537 |
+| 0.0627        | 3.0090 | 1005 | 0.2828          | 16.0331 |
+| 0.0262        | 3.0539 | 1020 | 0.3084          | 15.0202 |
+| 0.0266        | 3.0988 | 1035 | 0.3129          | 16.9708 |
+| 0.024         | 3.1437 | 1050 | 0.3114          | 14.9722 |
+| 0.0271        | 3.1886 | 1065 | 0.3152          | 14.5416 |
+| 0.026         | 3.2335 | 1080 | 0.3135          | 16.4533 |
+| 0.0281        | 3.2784 | 1095 | 0.3151          | 17.0123 |
+| 0.0295        | 3.3234 | 1110 | 0.3160          | 15.4183 |
+| 0.0259        | 3.3683 | 1125 | 0.3101          | 14.8269 |
+| 0.0276        | 3.4132 | 1140 | 0.3194          | 14.1175 |
+| 0.0271        | 3.4581 | 1155 | 0.3172          | 17.3314 |
+| 0.0304        | 3.5030 | 1170 | 0.3111          | 18.0577 |
+| 0.0268        | 3.5479 | 1185 | 0.3129          | 14.0928 |
+| 0.0256        | 3.5928 | 1200 | 0.3083          | 14.7374 |
+| 0.0281        | 3.6377 | 1215 | 0.3079          | 14.9125 |
+| 0.0274        | 3.6826 | 1230 | 0.3180          | 14.4586 |
+| 0.0282        | 3.7275 | 1245 | 0.3091          | 14.6622 |
+| 0.0224        | 3.7725 | 1260 | 0.3139          | 14.4132 |
+| 0.0254        | 3.8174 | 1275 | 0.3141          | 14.0747 |
+| 0.0279        | 3.8623 | 1290 | 0.3110          | 18.3676 |
+| 0.0245        | 3.9072 | 1305 | 0.3119          | 15.0565 |
+| 0.0256        | 3.9521 | 1320 | 0.3149          | 16.3560 |
+| 0.0273        | 3.9970 | 1335 | 0.3128          | 16.3405 |
+| 0.0126        | 4.0419 | 1350 | 0.3265          | 14.9385 |
+| 0.0087        | 4.0868 | 1365 | 0.3411          | 14.4547 |
+| 0.009         | 4.1317 | 1380 | 0.3394          | 14.6298 |
+| 0.0093        | 4.1766 | 1395 | 0.3424          | 14.4547 |
+| 0.0082        | 4.2216 | 1410 | 0.3457          | 14.4780 |
+| 0.0093        | 4.2665 | 1425 | 0.3472          | 13.8192 |
+| 0.0072        | 4.3114 | 1440 | 0.3491          | 15.0189 |
+| 0.0093        | 4.3563 | 1455 | 0.3490          | 16.3962 |
+| 0.0098        | 4.4012 | 1470 | 0.3455          | 16.3755 |
+| 0.0077        | 4.4461 | 1485 | 0.3429          | 16.9410 |
+| 0.0089        | 4.4910 | 1500 | 0.3452          | 17.0966 |
+| 0.0099        | 4.5359 | 1515 | 0.3469          | 18.3897 |
+| 0.0066        | 4.5808 | 1530 | 0.3465          | 19.0083 |
+| 0.0074        | 4.6257 | 1545 | 0.3455          | 19.6867 |
+| 0.0069        | 4.6707 | 1560 | 0.3489          | 18.5440 |
+| 0.008         | 4.7156 | 1575 | 0.3502          | 18.4078 |
+| 0.0079        | 4.7605 | 1590 | 0.3503          | 18.1057 |
+| 0.0077        | 4.8054 | 1605 | 0.3501          | 18.2574 |
+| 0.0058        | 4.8503 | 1620 | 0.3492          | 18.1653 |
+| 0.0076        | 4.8952 | 1635 | 0.3486          | 17.7905 |
+| 0.0064        | 4.9401 | 1650 | 0.3487          | 17.3858 |
+| 0.0057        | 4.9850 | 1665 | 0.3489          | 17.3755 |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

generation_config.json

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+}

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