End of training
Browse files- README.md +43 -76
- adapter_model.bin +1 -1
- training_args.bin +2 -2
README.md
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tags:
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- generated_from_trainer
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model-index:
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- name: Sentiment-google-t5-v1_1-large-intra_model
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Sentiment-google-t5-v1_1-large-intra_model
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This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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| 3.635 | 40.0 | 1760 | 3.8308 |
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| 3.5791 | 41.0 | 1804 | 3.7949 |
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| 3.5878 | 42.0 | 1848 | 3.6340 |
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| 1.9533 | 43.0 | 1892 | 1.6975 |
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| 1.3746 | 44.0 | 1936 | 0.9731 |
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| 1.1216 | 45.0 | 1980 | 0.8581 |
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| 1.0273 | 46.0 | 2024 | 0.7932 |
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| 0.9245 | 47.0 | 2068 | 0.6956 |
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| 0.8437 | 48.0 | 2112 | 0.6750 |
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| 0.8431 | 49.0 | 2156 | 0.6681 |
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| 0.8127 | 50.0 | 2200 | 0.6492 |
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| 0.7827 | 51.0 | 2244 | 0.6452 |
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| 0.7643 | 52.0 | 2288 | 0.6512 |
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| 0.7748 | 53.0 | 2332 | 0.6544 |
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| 0.7677 | 54.0 | 2376 | 0.6353 |
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| 0.7714 | 55.0 | 2420 | 0.6341 |
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| 0.7433 | 56.0 | 2464 | 0.6338 |
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| 0.7511 | 57.0 | 2508 | 0.6347 |
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| 0.7492 | 58.0 | 2552 | 0.6594 |
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| 0.7479 | 59.0 | 2596 | 0.6441 |
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| 0.7434 | 60.0 | 2640 | 0.6307 |
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| 0.7184 | 61.0 | 2684 | 0.6313 |
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| 0.7339 | 62.0 | 2728 | 0.6293 |
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| 0.7617 | 63.0 | 2772 | 0.6282 |
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| 0.7382 | 64.0 | 2816 | 0.6304 |
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| 0.7236 | 65.0 | 2860 | 0.6272 |
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| 0.7333 | 66.0 | 2904 | 0.6281 |
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| 0.7155 | 67.0 | 2948 | 0.6269 |
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| 0.726 | 68.0 | 2992 | 0.6299 |
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| 0.7463 | 69.0 | 3036 | 0.6287 |
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| 0.7202 | 70.0 | 3080 | 0.6278 |
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| 0.7402 | 71.0 | 3124 | 0.6293 |
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| 0.7418 | 72.0 | 3168 | 0.6325 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.
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- Tokenizers 0.14.1
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tags:
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- generated_from_trainer
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model-index:
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- name: Sentiment-google-t5-v1_1-large-intra_model-frequency-model_annots_str
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Sentiment-google-t5-v1_1-large-intra_model-frequency-model_annots_str
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This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6025
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 20.2785 | 1.0 | 44 | 24.1630 |
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| 16.5089 | 2.0 | 88 | 12.6240 |
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| 12.1856 | 3.0 | 132 | 9.5483 |
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| 9.6054 | 4.0 | 176 | 9.1792 |
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| 8.6106 | 5.0 | 220 | 8.9367 |
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| 8.4152 | 6.0 | 264 | 8.7252 |
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| 8.3046 | 7.0 | 308 | 8.5101 |
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| 7.8895 | 8.0 | 352 | 8.1848 |
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| 7.7099 | 9.0 | 396 | 7.7711 |
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| 7.3027 | 10.0 | 440 | 7.4309 |
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| 7.1553 | 11.0 | 484 | 7.2568 |
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| 6.9202 | 12.0 | 528 | 7.1566 |
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| 6.8527 | 13.0 | 572 | 7.0624 |
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| 6.5631 | 14.0 | 616 | 6.8983 |
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| 1.0138 | 15.0 | 660 | 0.7973 |
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| 0.8985 | 16.0 | 704 | 0.7822 |
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| 0.8793 | 17.0 | 748 | 0.7791 |
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| 0.8737 | 18.0 | 792 | 0.7799 |
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| 0.8562 | 19.0 | 836 | 0.7812 |
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| 0.8563 | 20.0 | 880 | 0.7742 |
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| 0.8498 | 21.0 | 924 | 0.7738 |
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| 0.8316 | 22.0 | 968 | 0.7683 |
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| 0.8281 | 23.0 | 1012 | 0.7688 |
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| 0.8314 | 24.0 | 1056 | 0.7732 |
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| 0.8161 | 25.0 | 1100 | 0.7660 |
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| 0.8273 | 26.0 | 1144 | 0.7634 |
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| 0.8314 | 27.0 | 1188 | 0.7622 |
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| 0.828 | 28.0 | 1232 | 0.7625 |
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| 0.8161 | 29.0 | 1276 | 0.7605 |
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| 0.812 | 30.0 | 1320 | 0.7602 |
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| 0.8126 | 31.0 | 1364 | 0.7580 |
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| 0.8021 | 32.0 | 1408 | 0.7649 |
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| 0.7973 | 33.0 | 1452 | 0.7588 |
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| 0.8076 | 34.0 | 1496 | 0.7569 |
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| 0.819 | 35.0 | 1540 | 0.7559 |
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| 0.8069 | 36.0 | 1584 | 0.7540 |
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| 0.8042 | 37.0 | 1628 | 0.7546 |
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| 0.8054 | 38.0 | 1672 | 0.7579 |
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| 0.8049 | 39.0 | 1716 | 0.7584 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.6.1
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- Tokenizers 0.14.1
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adapter_model.bin
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size 4825098
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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