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flan-t5-xl-absa-rest

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  1. README.md +13 -15
  2. adapter_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -2,8 +2,6 @@
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  base_model: ybelkada/flan-t5-xl-sharded-bf16
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  tags:
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  - generated_from_trainer
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- datasets:
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- - sem_eval2014_task4
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  model-index:
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  - name: flan-t5-xl-absa-rest
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  results: []
@@ -14,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # flan-t5-xl-absa-rest
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- This model is a fine-tuned version of [ybelkada/flan-t5-xl-sharded-bf16](https://huggingface.co/ybelkada/flan-t5-xl-sharded-bf16) on the sem_eval2014_task4 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1705
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  ## Model description
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@@ -48,17 +46,17 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.4491 | 0.9 | 200 | 0.7559 |
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- | 0.4855 | 1.8 | 400 | 0.2962 |
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- | 0.3356 | 2.7 | 600 | 0.2460 |
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- | 0.2742 | 3.6 | 800 | 0.2234 |
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- | 0.2529 | 4.5 | 1000 | 0.2087 |
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- | 0.2381 | 5.41 | 1200 | 0.1907 |
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- | 0.217 | 6.31 | 1400 | 0.1844 |
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- | 0.2101 | 7.21 | 1600 | 0.1796 |
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- | 0.2113 | 8.11 | 1800 | 0.1737 |
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- | 0.2026 | 9.01 | 2000 | 0.1722 |
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- | 0.1988 | 9.91 | 2200 | 0.1705 |
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  ### Framework versions
 
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  base_model: ybelkada/flan-t5-xl-sharded-bf16
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: flan-t5-xl-absa-rest
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  results: []
 
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  # flan-t5-xl-absa-rest
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+ This model is a fine-tuned version of [ybelkada/flan-t5-xl-sharded-bf16](https://huggingface.co/ybelkada/flan-t5-xl-sharded-bf16) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1525
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.4491 | 0.9 | 200 | 0.6438 |
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+ | 0.5032 | 1.8 | 400 | 0.2452 |
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+ | 0.3266 | 2.7 | 600 | 0.2064 |
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+ | 0.2723 | 3.6 | 800 | 0.1891 |
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+ | 0.2546 | 4.5 | 1000 | 0.1692 |
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+ | 0.2286 | 5.41 | 1200 | 0.1697 |
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+ | 0.2253 | 6.31 | 1400 | 0.1638 |
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+ | 0.2076 | 7.21 | 1600 | 0.1586 |
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+ | 0.2036 | 8.11 | 1800 | 0.1544 |
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+ | 0.1982 | 9.01 | 2000 | 0.1524 |
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+ | 0.1952 | 9.91 | 2200 | 0.1525 |
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  ### Framework versions
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