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ndemoes
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distilgpt2-finetuned-eap

Text Generation
Transformers
TensorFlow
gpt2
generated_from_keras_callback
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add model

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  1. README.md +58 -16
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,9 +14,11 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 2.2171
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- - Validation Loss: 5.3472
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- - Epoch: 9
 
 
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  ## Model description
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@@ -40,23 +42,63 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Train Loss | Validation Loss | Epoch |
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- |:----------:|:---------------:|:-----:|
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- | 3.9459 | 4.3483 | 0 |
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- | 3.7441 | 4.3673 | 1 |
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- | 3.5493 | 4.4316 | 2 |
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- | 3.3524 | 4.4821 | 3 |
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- | 3.1628 | 4.5738 | 4 |
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- | 2.9695 | 4.6879 | 5 |
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- | 2.7818 | 4.8299 | 6 |
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- | 2.5856 | 4.9463 | 7 |
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- | 2.3977 | 5.1645 | 8 |
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- | 2.2171 | 5.3472 | 9 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.21.1
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- - TensorFlow 2.9.1
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  - Datasets 2.4.0
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  - Tokenizers 0.12.1
 
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  This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.3557
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+ - Train Accuracy: 0.0010
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+ - Validation Loss: 7.4820
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+ - Validation Accuracy: 0.0
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+ - Epoch: 49
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  ## Model description
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  ### Training results
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+ | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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+ |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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+ | 4.6280 | 0.0015 | 4.3578 | 0.0013 | 0 |
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+ | 4.2572 | 0.0018 | 4.2845 | 0.0013 | 1 |
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+ | 4.0662 | 0.0018 | 4.2587 | 0.0012 | 2 |
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+ | 3.9066 | 0.0016 | 4.2470 | 0.0012 | 3 |
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+ | 3.7578 | 0.0016 | 4.2493 | 0.0013 | 4 |
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+ | 3.6177 | 0.0018 | 4.2728 | 0.0013 | 5 |
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+ | 3.4741 | 0.0017 | 4.3208 | 0.0012 | 6 |
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+ | 3.3366 | 0.0017 | 4.3542 | 0.0012 | 7 |
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+ | 3.1946 | 0.0016 | 4.3973 | 0.0012 | 8 |
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+ | 3.0581 | 0.0016 | 4.4947 | 0.0014 | 9 |
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+ | 2.9171 | 0.0017 | 4.5970 | 0.0013 | 10 |
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+ | 2.7766 | 0.0016 | 4.6691 | 0.0014 | 11 |
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+ | 2.6373 | 0.0015 | 4.7961 | 0.0012 | 12 |
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+ | 2.4986 | 0.0014 | 4.8906 | 0.0002 | 13 |
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+ | 2.3600 | 0.0015 | 4.9836 | 0.0002 | 14 |
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+ | 2.2307 | 0.0014 | 5.1439 | 0.0001 | 15 |
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+ | 2.1054 | 0.0015 | 5.3017 | 0.0001 | 16 |
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+ | 1.9798 | 0.0015 | 5.4037 | 0.0001 | 17 |
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+ | 1.8679 | 0.0014 | 5.5184 | 0.0001 | 18 |
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+ | 1.7544 | 0.0013 | 5.6429 | 0.0001 | 19 |
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+ | 1.6486 | 0.0013 | 5.7368 | 0.0001 | 20 |
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+ | 1.5492 | 0.0013 | 5.8070 | 0.0001 | 21 |
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+ | 1.4525 | 0.0013 | 5.9248 | 0.0001 | 22 |
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+ | 1.3725 | 0.0013 | 5.9879 | 0.0 | 23 |
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+ | 1.2901 | 0.0011 | 6.1063 | 0.0001 | 24 |
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+ | 1.2178 | 0.0014 | 6.1828 | 0.0001 | 25 |
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+ | 1.1429 | 0.0012 | 6.2581 | 0.0001 | 26 |
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+ | 1.0831 | 0.0011 | 6.3003 | 0.0000 | 27 |
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+ | 1.0266 | 0.0012 | 6.3558 | 0.0001 | 28 |
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+ | 0.9673 | 0.0012 | 6.4831 | 0.0000 | 29 |
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+ | 0.9116 | 0.0012 | 6.5555 | 0.0 | 30 |
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+ | 0.8652 | 0.0012 | 6.6239 | 0.0 | 31 |
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+ | 0.8198 | 0.0013 | 6.6751 | 0.0 | 32 |
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+ | 0.7795 | 0.0013 | 6.7499 | 0.0 | 33 |
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+ | 0.7410 | 0.0010 | 6.7741 | 0.0000 | 34 |
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+ | 0.7015 | 0.0012 | 6.8395 | 0.0000 | 35 |
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+ | 0.6679 | 0.0011 | 6.9150 | 0.0 | 36 |
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+ | 0.6367 | 0.0010 | 6.9847 | 0.0 | 37 |
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+ | 0.6034 | 0.0011 | 7.0334 | 0.0001 | 38 |
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+ | 0.5756 | 0.0010 | 7.0516 | 0.0000 | 39 |
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+ | 0.5442 | 0.0011 | 7.1220 | 0.0 | 40 |
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+ | 0.5188 | 0.0010 | 7.1494 | 0.0000 | 41 |
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+ | 0.4971 | 0.0010 | 7.2100 | 0.0 | 42 |
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+ | 0.4711 | 0.0010 | 7.2883 | 0.0001 | 43 |
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+ | 0.4501 | 0.0011 | 7.2946 | 0.0 | 44 |
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+ | 0.4274 | 0.0011 | 7.3313 | 0.0001 | 45 |
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+ | 0.4066 | 0.0011 | 7.3620 | 0.0000 | 46 |
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+ | 0.3898 | 0.0011 | 7.4119 | 0.0000 | 47 |
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+ | 0.3679 | 0.0010 | 7.4769 | 0.0001 | 48 |
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+ | 0.3557 | 0.0010 | 7.4820 | 0.0 | 49 |
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  ### Framework versions
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  - Transformers 4.21.1
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+ - TensorFlow 2.8.2
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  - Datasets 2.4.0
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  - Tokenizers 0.12.1
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