Model save

README.md

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+---
+base_model: google/pegasus-xsum
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- precision
+- recall
+- f1
+model-index:
+- name: LLM_Teached_Pegasus_50k
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# LLM_Teached_Pegasus_50k
+
+This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7193
+- Rouge1: 0.4541
+- Rouge2: 0.2071
+- Rougel: 0.3708
+- Rougelsum: 0.3708
+- Gen Len: 26.4531
+- Precision: 0.9082
+- Recall: 0.9061
+- F1: 0.907
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 390  | 1.8258          | 0.4338 | 0.1906 | 0.3496 | 0.3498    | 26.2967 | 0.9049    | 0.9023 | 0.9034 |
+| 2.1621        | 2.0   | 781  | 1.7537          | 0.4449 | 0.2005 | 0.3633 | 0.3633    | 26.2727 | 0.9068    | 0.9044 | 0.9054 |
+| 1.8794        | 3.0   | 1172 | 1.7268          | 0.4518 | 0.2061 | 0.3696 | 0.3695    | 26.4345 | 0.9078    | 0.9058 | 0.9066 |
+| 1.8271        | 3.99  | 1560 | 1.7193          | 0.4541 | 0.2071 | 0.3708 | 0.3708    | 26.4531 | 0.9082    | 0.9061 | 0.907  |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.15.0

generation_config.json

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+{
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+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 1,
+  "length_penalty": 0.6,
+  "max_length": 64,
+  "num_beams": 8,
+  "pad_token_id": 0,
+  "transformers_version": "4.36.0"
+}

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