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rhaymison
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t5-portuguese-small-summarization

Summarization
Transformers
Safetensors
Portuguese
t5
text2text-generation
Generated from Trainer
text2text
text-generation-inference
Inference Endpoints
Model card Files Community
rhaymison commited on
Commit
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1 Parent(s): 9a225ca

End of training

Browse files
Files changed (3) hide show
  1. README.md +47 -52
  2. model.safetensors +1 -1
  3. tokenizer.json +1 -6
README.md CHANGED
@@ -8,11 +8,6 @@ metrics:
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  model-index:
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  - name: flan-t5-small-summarization
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  results: []
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- pipeline_tag: text2text-generation
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- inference:
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- parameters:
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- max_new_tokens: 128
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- temperature: 0.7
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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
@@ -22,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9716
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- - Rouge1: 14.8237
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- - Rouge2: 5.3275
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- - Rougel: 12.6729
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- - Rougelsum: 13.6266
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  - Gen Len: 18.968
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  ## Model description
@@ -61,47 +56,47 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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- | No log | 0.12 | 100 | 2.0773 | 15.1231 | 5.4025 | 12.9496 | 13.9319 | 18.94 |
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- | No log | 0.24 | 200 | 2.0736 | 14.7565 | 5.2799 | 12.6268 | 13.5578 | 18.94 |
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- | No log | 0.36 | 300 | 2.0632 | 14.8383 | 5.2319 | 12.6555 | 13.6597 | 18.968 |
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- | No log | 0.48 | 400 | 2.0629 | 14.8558 | 5.2815 | 12.6581 | 13.6503 | 18.968 |
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- | 2.2157 | 0.6 | 500 | 2.0583 | 14.8736 | 5.3228 | 12.649 | 13.6717 | 18.968 |
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- | 2.2157 | 0.72 | 600 | 2.0520 | 14.8178 | 5.3112 | 12.586 | 13.6262 | 18.968 |
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- | 2.2157 | 0.84 | 700 | 2.0467 | 14.9042 | 5.3468 | 12.6543 | 13.6596 | 18.968 |
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- | 2.2157 | 0.96 | 800 | 2.0435 | 14.8682 | 5.3287 | 12.661 | 13.6869 | 18.968 |
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- | 2.2157 | 1.08 | 900 | 2.0375 | 14.9469 | 5.362 | 12.7083 | 13.7525 | 18.968 |
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- | 2.1846 | 1.2 | 1000 | 2.0324 | 14.8316 | 5.3471 | 12.6593 | 13.6452 | 18.968 |
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- | 2.1846 | 1.32 | 1100 | 2.0309 | 14.6717 | 5.2555 | 12.5319 | 13.4962 | 18.968 |
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- | 2.1846 | 1.44 | 1200 | 2.0189 | 14.8455 | 5.3386 | 12.6002 | 13.6588 | 18.968 |
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- | 2.1846 | 1.56 | 1300 | 2.0182 | 14.9323 | 5.3902 | 12.7187 | 13.7579 | 18.968 |
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- | 2.1846 | 1.68 | 1400 | 2.0172 | 14.969 | 5.4698 | 12.8021 | 13.8116 | 18.968 |
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- | 2.1596 | 1.8 | 1500 | 2.0105 | 15.0152 | 5.5355 | 12.8098 | 13.8475 | 18.968 |
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- | 2.1596 | 1.92 | 1600 | 2.0100 | 15.0009 | 5.3835 | 12.764 | 13.785 | 18.968 |
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- | 2.1596 | 2.04 | 1700 | 2.0083 | 14.8145 | 5.2912 | 12.6179 | 13.6279 | 18.968 |
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- | 2.1596 | 2.16 | 1800 | 2.0035 | 14.8232 | 5.2131 | 12.6386 | 13.6297 | 18.968 |
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- | 2.1596 | 2.28 | 1900 | 2.0006 | 14.8076 | 5.2617 | 12.6578 | 13.6631 | 18.968 |
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- | 2.1405 | 2.4 | 2000 | 1.9983 | 14.6508 | 5.0855 | 12.4956 | 13.4989 | 18.968 |
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- | 2.1405 | 2.52 | 2100 | 1.9965 | 14.9548 | 5.2857 | 12.6947 | 13.7664 | 18.968 |
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- | 2.1405 | 2.64 | 2200 | 1.9917 | 14.8786 | 5.2212 | 12.6813 | 13.6609 | 18.968 |
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- | 2.1405 | 2.76 | 2300 | 1.9904 | 15.0902 | 5.4835 | 12.8911 | 13.9191 | 18.968 |
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- | 2.1405 | 2.88 | 2400 | 1.9880 | 14.8188 | 5.2057 | 12.6325 | 13.6335 | 18.968 |
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- | 2.1287 | 3.0 | 2500 | 1.9844 | 14.7362 | 5.2487 | 12.6559 | 13.64 | 18.968 |
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- | 2.1287 | 3.12 | 2600 | 1.9834 | 14.9356 | 5.3404 | 12.7325 | 13.7185 | 18.968 |
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- | 2.1287 | 3.24 | 2700 | 1.9839 | 14.9543 | 5.4587 | 12.757 | 13.767 | 18.968 |
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- | 2.1287 | 3.36 | 2800 | 1.9821 | 14.8174 | 5.2522 | 12.6935 | 13.6292 | 18.968 |
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- | 2.1287 | 3.48 | 2900 | 1.9816 | 14.8201 | 5.2606 | 12.6679 | 13.6275 | 18.968 |
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- | 2.1149 | 3.6 | 3000 | 1.9795 | 14.8112 | 5.253 | 12.5789 | 13.5714 | 18.968 |
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- | 2.1149 | 3.72 | 3100 | 1.9788 | 14.7946 | 5.3272 | 12.6237 | 13.614 | 18.968 |
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- | 2.1149 | 3.84 | 3200 | 1.9761 | 14.8197 | 5.295 | 12.6209 | 13.6327 | 18.968 |
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- | 2.1149 | 3.96 | 3300 | 1.9761 | 14.7752 | 5.2759 | 12.6239 | 13.6167 | 18.968 |
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- | 2.1149 | 4.08 | 3400 | 1.9714 | 14.7938 | 5.2988 | 12.7085 | 13.6708 | 18.968 |
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- | 2.1138 | 4.2 | 3500 | 1.9729 | 14.8006 | 5.2526 | 12.6427 | 13.6018 | 18.968 |
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- | 2.1138 | 4.32 | 3600 | 1.9751 | 14.7531 | 5.2913 | 12.6372 | 13.5782 | 18.968 |
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- | 2.1138 | 4.44 | 3700 | 1.9743 | 14.7556 | 5.2694 | 12.6372 | 13.5786 | 18.968 |
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- | 2.1138 | 4.56 | 3800 | 1.9710 | 14.8124 | 5.2887 | 12.7095 | 13.6666 | 18.968 |
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- | 2.1138 | 4.68 | 3900 | 1.9725 | 14.7104 | 5.2357 | 12.5839 | 13.5364 | 18.968 |
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- | 2.1033 | 4.8 | 4000 | 1.9726 | 14.7673 | 5.2771 | 12.6343 | 13.5731 | 18.968 |
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- | 2.1033 | 4.92 | 4100 | 1.9716 | 14.8237 | 5.3275 | 12.6729 | 13.6266 | 18.968 |
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  ### Framework versions
@@ -109,4 +104,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  model-index:
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  - name: flan-t5-small-summarization
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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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  This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8997
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+ - Rouge1: 15.0817
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+ - Rouge2: 5.3292
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+ - Rougel: 12.958
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+ - Rougelsum: 13.8768
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  - Gen Len: 18.968
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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+ | No log | 0.12 | 100 | 1.9634 | 14.8269 | 5.3829 | 12.7816 | 13.7008 | 18.968 |
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+ | No log | 0.24 | 200 | 1.9644 | 14.9042 | 5.4617 | 12.7989 | 13.7004 | 18.968 |
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+ | No log | 0.36 | 300 | 1.9590 | 14.7014 | 5.1896 | 12.6361 | 13.5061 | 18.968 |
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+ | No log | 0.48 | 400 | 1.9592 | 14.8482 | 5.2667 | 12.6819 | 13.6022 | 18.968 |
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+ | 2.092 | 0.6 | 500 | 1.9551 | 14.6613 | 5.2159 | 12.5685 | 13.4544 | 18.968 |
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+ | 2.092 | 0.72 | 600 | 1.9508 | 14.6862 | 5.2585 | 12.6345 | 13.5299 | 18.968 |
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+ | 2.092 | 0.84 | 700 | 1.9473 | 14.7323 | 5.1636 | 12.6962 | 13.5118 | 18.968 |
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+ | 2.092 | 0.96 | 800 | 1.9488 | 14.7104 | 5.1587 | 12.7019 | 13.5439 | 18.968 |
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+ | 2.092 | 1.08 | 900 | 1.9397 | 14.8448 | 5.2826 | 12.7924 | 13.6464 | 18.968 |
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+ | 2.077 | 1.2 | 1000 | 1.9373 | 14.9495 | 5.3975 | 12.8935 | 13.7491 | 18.968 |
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+ | 2.077 | 1.32 | 1100 | 1.9372 | 14.93 | 5.4048 | 12.8809 | 13.7012 | 18.968 |
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+ | 2.077 | 1.44 | 1200 | 1.9311 | 14.8196 | 5.2564 | 12.8279 | 13.6688 | 18.968 |
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+ | 2.077 | 1.56 | 1300 | 1.9311 | 14.8757 | 5.2282 | 12.8286 | 13.7152 | 18.968 |
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+ | 2.077 | 1.68 | 1400 | 1.9287 | 14.9308 | 5.3154 | 12.8522 | 13.7326 | 18.968 |
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+ | 2.06 | 1.8 | 1500 | 1.9268 | 14.8923 | 5.2594 | 12.8387 | 13.6839 | 18.968 |
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+ | 2.06 | 1.92 | 1600 | 1.9256 | 15.085 | 5.2911 | 12.9424 | 13.8375 | 18.968 |
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+ | 2.06 | 2.04 | 1700 | 1.9245 | 14.9127 | 5.3024 | 12.8339 | 13.6987 | 18.968 |
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+ | 2.06 | 2.16 | 1800 | 1.9197 | 15.0974 | 5.2812 | 12.9218 | 13.8758 | 18.968 |
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+ | 2.06 | 2.28 | 1900 | 1.9172 | 15.0564 | 5.2437 | 12.8736 | 13.8318 | 18.968 |
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+ | 2.0474 | 2.4 | 2000 | 1.9149 | 14.9414 | 5.1408 | 12.8381 | 13.7028 | 18.968 |
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+ | 2.0474 | 2.52 | 2100 | 1.9149 | 15.0211 | 5.2195 | 12.954 | 13.809 | 18.968 |
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+ | 2.0474 | 2.64 | 2200 | 1.9113 | 15.0689 | 5.2702 | 12.9338 | 13.8276 | 18.968 |
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+ | 2.0474 | 2.76 | 2300 | 1.9129 | 15.134 | 5.2675 | 13.0113 | 13.9106 | 18.968 |
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+ | 2.0474 | 2.88 | 2400 | 1.9103 | 15.1097 | 5.276 | 12.9856 | 13.8559 | 18.968 |
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+ | 2.04 | 3.0 | 2500 | 1.9062 | 15.1413 | 5.2281 | 12.9537 | 13.8494 | 18.968 |
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+ | 2.04 | 3.12 | 2600 | 1.9070 | 14.9792 | 5.2091 | 12.8586 | 13.695 | 18.968 |
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+ | 2.04 | 3.24 | 2700 | 1.9066 | 14.9506 | 5.2238 | 12.8265 | 13.6925 | 18.968 |
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+ | 2.04 | 3.36 | 2800 | 1.9063 | 15.053 | 5.2235 | 12.8833 | 13.7711 | 18.968 |
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+ | 2.04 | 3.48 | 2900 | 1.9064 | 14.9386 | 5.1363 | 12.7915 | 13.688 | 18.968 |
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+ | 2.0273 | 3.6 | 3000 | 1.9053 | 15.0901 | 5.2518 | 12.9063 | 13.8338 | 18.968 |
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+ | 2.0273 | 3.72 | 3100 | 1.9059 | 15.0692 | 5.2665 | 12.932 | 13.8394 | 18.968 |
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+ | 2.0273 | 3.84 | 3200 | 1.9021 | 15.0768 | 5.3179 | 12.9916 | 13.8653 | 18.968 |
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+ | 2.0273 | 3.96 | 3300 | 1.9024 | 15.1808 | 5.3312 | 13.0143 | 13.9269 | 18.968 |
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+ | 2.0273 | 4.08 | 3400 | 1.8981 | 15.0905 | 5.2769 | 12.9551 | 13.8666 | 18.968 |
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+ | 2.0291 | 4.2 | 3500 | 1.9007 | 15.0453 | 5.3159 | 12.9429 | 13.824 | 18.968 |
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+ | 2.0291 | 4.32 | 3600 | 1.9017 | 15.0403 | 5.3474 | 12.9625 | 13.8437 | 18.968 |
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+ | 2.0291 | 4.44 | 3700 | 1.9005 | 15.0456 | 5.3468 | 12.9521 | 13.8413 | 18.968 |
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+ | 2.0291 | 4.56 | 3800 | 1.8991 | 15.0501 | 5.3539 | 12.9597 | 13.8408 | 18.968 |
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+ | 2.0291 | 4.68 | 3900 | 1.8998 | 15.1219 | 5.3599 | 12.9936 | 13.9013 | 18.968 |
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+ | 2.0193 | 4.8 | 4000 | 1.9004 | 15.0831 | 5.329 | 12.9697 | 13.8762 | 18.968 |
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+ | 2.0193 | 4.92 | 4100 | 1.8997 | 15.0817 | 5.3292 | 12.958 | 13.8768 | 18.968 |
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  ### Framework versions
 
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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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  "padding": null,
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