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limaatulya
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my_awesome_billsum_model_80

Text2Text Generation
Transformers
TensorBoard
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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End of training

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  1. README.md +164 -0
  2. generation_config.json +6 -0
  3. model.safetensors +1 -1
  4. runs/Jun23_10-22-48_5356998822ef/events.out.tfevents.1719138169.5356998822ef.11152.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google-t5/t5-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: my_awesome_billsum_model_80
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+ results: []
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+ ---
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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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+
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+ # my_awesome_billsum_model_80
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+
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+ This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1923
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+ - Rouge1: 0.9697
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+ - Rouge2: 0.8445
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+ - Rougel: 0.9199
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+ - Rougelsum: 0.9179
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+ - Gen Len: 4.9583
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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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 | 1.0 | 12 | 2.0545 | 0.4101 | 0.2839 | 0.3907 | 0.3895 | 16.8125 |
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+ | No log | 2.0 | 24 | 1.4437 | 0.442 | 0.3195 | 0.4261 | 0.4245 | 15.9583 |
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+ | No log | 3.0 | 36 | 0.8267 | 0.5727 | 0.4315 | 0.541 | 0.5416 | 12.8125 |
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+ | No log | 4.0 | 48 | 0.5186 | 0.9583 | 0.8429 | 0.9113 | 0.91 | 5.25 |
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+ | No log | 5.0 | 60 | 0.4535 | 0.9739 | 0.8607 | 0.9276 | 0.9271 | 4.875 |
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+ | No log | 6.0 | 72 | 0.4258 | 0.9769 | 0.8768 | 0.9365 | 0.9365 | 4.8958 |
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+ | No log | 7.0 | 84 | 0.4014 | 0.9798 | 0.8869 | 0.9454 | 0.9464 | 4.9167 |
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+ | No log | 8.0 | 96 | 0.3779 | 0.9798 | 0.8869 | 0.9454 | 0.9464 | 4.9167 |
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+ | No log | 9.0 | 108 | 0.3663 | 0.9769 | 0.8726 | 0.9365 | 0.9375 | 4.9375 |
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+ | No log | 10.0 | 120 | 0.3554 | 0.9687 | 0.8444 | 0.922 | 0.9226 | 5.0 |
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+ | No log | 11.0 | 132 | 0.3461 | 0.9687 | 0.8444 | 0.922 | 0.9226 | 5.0 |
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+ | No log | 12.0 | 144 | 0.3339 | 0.9716 | 0.8569 | 0.9314 | 0.9314 | 4.9792 |
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+ | No log | 13.0 | 156 | 0.3242 | 0.9716 | 0.8569 | 0.9314 | 0.9314 | 4.9792 |
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+ | No log | 14.0 | 168 | 0.3155 | 0.9716 | 0.8569 | 0.9314 | 0.9314 | 4.9792 |
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+ | No log | 15.0 | 180 | 0.3030 | 0.9716 | 0.8569 | 0.9314 | 0.9314 | 4.9792 |
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+ | No log | 16.0 | 192 | 0.2979 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 17.0 | 204 | 0.2957 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 18.0 | 216 | 0.2950 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 19.0 | 228 | 0.2840 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 20.0 | 240 | 0.2778 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 21.0 | 252 | 0.2662 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 22.0 | 264 | 0.2609 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 23.0 | 276 | 0.2587 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 24.0 | 288 | 0.2567 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 25.0 | 300 | 0.2604 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 26.0 | 312 | 0.2540 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 27.0 | 324 | 0.2514 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 28.0 | 336 | 0.2437 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 29.0 | 348 | 0.2370 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 30.0 | 360 | 0.2369 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 31.0 | 372 | 0.2347 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 32.0 | 384 | 0.2329 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 33.0 | 396 | 0.2327 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 34.0 | 408 | 0.2271 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 35.0 | 420 | 0.2231 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 36.0 | 432 | 0.2177 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 37.0 | 444 | 0.2168 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 38.0 | 456 | 0.2154 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | No log | 39.0 | 468 | 0.2187 | 0.9676 | 0.8361 | 0.9193 | 0.9173 | 5.0 |
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+ | No log | 40.0 | 480 | 0.2202 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | No log | 41.0 | 492 | 0.2164 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 42.0 | 504 | 0.2160 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 43.0 | 516 | 0.2179 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 44.0 | 528 | 0.2182 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 45.0 | 540 | 0.2206 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 46.0 | 552 | 0.2172 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 47.0 | 564 | 0.2128 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 48.0 | 576 | 0.2194 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 49.0 | 588 | 0.2204 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 50.0 | 600 | 0.2124 | 0.971 | 0.8468 | 0.9222 | 0.9202 | 4.9583 |
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+ | 0.4771 | 51.0 | 612 | 0.2136 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 52.0 | 624 | 0.2119 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 53.0 | 636 | 0.2085 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 54.0 | 648 | 0.2115 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 55.0 | 660 | 0.2133 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 56.0 | 672 | 0.2087 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 57.0 | 684 | 0.2057 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 58.0 | 696 | 0.2095 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.4771 | 59.0 | 708 | 0.2105 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 60.0 | 720 | 0.2123 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 61.0 | 732 | 0.2120 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 62.0 | 744 | 0.2132 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 63.0 | 756 | 0.2117 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 64.0 | 768 | 0.2068 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 65.0 | 780 | 0.2049 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 66.0 | 792 | 0.2054 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 67.0 | 804 | 0.2029 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 68.0 | 816 | 0.1995 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 69.0 | 828 | 0.1946 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 70.0 | 840 | 0.1975 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 71.0 | 852 | 0.1995 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 72.0 | 864 | 0.2009 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 73.0 | 876 | 0.2050 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 74.0 | 888 | 0.2039 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 75.0 | 900 | 0.2040 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 76.0 | 912 | 0.2020 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 77.0 | 924 | 0.2003 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 78.0 | 936 | 0.1992 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 79.0 | 948 | 0.1984 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 80.0 | 960 | 0.1971 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 81.0 | 972 | 0.1995 | 0.9675 | 0.8359 | 0.9136 | 0.9111 | 4.9792 |
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+ | 0.4771 | 82.0 | 984 | 0.2007 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.4771 | 83.0 | 996 | 0.2020 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 84.0 | 1008 | 0.2007 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 85.0 | 1020 | 0.1967 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 86.0 | 1032 | 0.1975 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 87.0 | 1044 | 0.1967 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 88.0 | 1056 | 0.1947 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 89.0 | 1068 | 0.1925 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 90.0 | 1080 | 0.1926 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 91.0 | 1092 | 0.1937 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 92.0 | 1104 | 0.1934 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 93.0 | 1116 | 0.1929 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 94.0 | 1128 | 0.1929 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 95.0 | 1140 | 0.1928 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 96.0 | 1152 | 0.1927 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 97.0 | 1164 | 0.1927 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 98.0 | 1176 | 0.1925 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 99.0 | 1188 | 0.1925 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+ | 0.113 | 100.0 | 1200 | 0.1923 | 0.9697 | 0.8445 | 0.9199 | 0.9179 | 4.9583 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
generation_config.json ADDED
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+ "decoder_start_token_id": 0,
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+ "eos_token_id": 1,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.41.2"
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