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LLM_Teached_Pegasus_FS

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  1. README.md +87 -0
  2. generation_config.json +11 -0
  3. model.safetensors +1 -1
  4. runs/Mar28_19-35-30_gde8xrctr1711261266898-zjnhj/events.out.tfevents.1711625733.gde8xrctr1711261266898-zjnhj.16654.0 +2 -2
README.md ADDED
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+ ---
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+ base_model: google/pegasus-large
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: LLM_Teached_Pegasus_FS
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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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+ # LLM_Teached_Pegasus_FS
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+
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+ This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6167
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+ - Rouge1: 0.4649
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+ - Rouge2: 0.2096
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+ - Rougel: 0.3686
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+ - Rougelsum: 0.3688
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+ - Gen Len: 30.6191
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+ - Precision: 0.9102
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+ - Recall: 0.9083
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+ - F1: 0.9091
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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: 24
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 96
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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: 16
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 208 | 1.8075 | 0.411 | 0.1689 | 0.3152 | 0.3155 | 29.9091 | 0.901 | 0.897 | 0.8988 |
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+ | No log | 2.0 | 417 | 1.7312 | 0.4379 | 0.1893 | 0.3442 | 0.3446 | 29.9073 | 0.9059 | 0.9024 | 0.904 |
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+ | 2.0112 | 3.0 | 625 | 1.6987 | 0.4475 | 0.1978 | 0.352 | 0.3525 | 30.0173 | 0.9075 | 0.9039 | 0.9055 |
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+ | 2.0112 | 4.0 | 834 | 1.6768 | 0.4514 | 0.1981 | 0.357 | 0.3573 | 30.0618 | 0.9082 | 0.9047 | 0.9063 |
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+ | 1.7647 | 5.0 | 1042 | 1.6617 | 0.4537 | 0.2003 | 0.3592 | 0.3595 | 30.3264 | 0.9084 | 0.9055 | 0.9068 |
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+ | 1.7647 | 6.0 | 1251 | 1.6502 | 0.4554 | 0.2021 | 0.3607 | 0.361 | 30.0827 | 0.9089 | 0.9057 | 0.9072 |
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+ | 1.7647 | 7.0 | 1459 | 1.6416 | 0.4592 | 0.2052 | 0.3639 | 0.3641 | 30.0218 | 0.9099 | 0.9064 | 0.908 |
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+ | 1.6948 | 8.0 | 1668 | 1.6360 | 0.4612 | 0.2054 | 0.3649 | 0.365 | 30.7827 | 0.909 | 0.9074 | 0.9081 |
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+ | 1.6948 | 9.0 | 1876 | 1.6302 | 0.4621 | 0.2062 | 0.3645 | 0.3647 | 30.6291 | 0.9095 | 0.9074 | 0.9083 |
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+ | 1.6501 | 10.0 | 2085 | 1.6265 | 0.4606 | 0.2051 | 0.3651 | 0.3655 | 30.4818 | 0.9095 | 0.9073 | 0.9083 |
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+ | 1.6501 | 11.0 | 2293 | 1.6230 | 0.4625 | 0.2073 | 0.3658 | 0.366 | 30.8064 | 0.9097 | 0.908 | 0.9087 |
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+ | 1.6222 | 12.0 | 2502 | 1.6205 | 0.4644 | 0.2082 | 0.3674 | 0.3679 | 30.5527 | 0.9103 | 0.9081 | 0.909 |
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+ | 1.6222 | 13.0 | 2710 | 1.6188 | 0.4648 | 0.2087 | 0.3681 | 0.3683 | 30.8055 | 0.9101 | 0.9083 | 0.909 |
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+ | 1.6222 | 14.0 | 2919 | 1.6172 | 0.4654 | 0.2097 | 0.3685 | 0.3689 | 30.6709 | 0.9104 | 0.9084 | 0.9093 |
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+ | 1.6048 | 15.0 | 3127 | 1.6169 | 0.465 | 0.21 | 0.3693 | 0.3697 | 30.6309 | 0.9104 | 0.9084 | 0.9093 |
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+ | 1.6048 | 15.96 | 3328 | 1.6167 | 0.4649 | 0.2096 | 0.3686 | 0.3688 | 30.6191 | 0.9102 | 0.9083 | 0.9091 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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+ - Tokenizers 0.15.0
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+ "pad_token_id": 0,
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+ "transformers_version": "4.36.0"
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+ }
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