Model save

README.md

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+---
+license: mit
+base_model: facebook/bart-large-xsum
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- precision
+- recall
+- f1
+model-index:
+- name: LLM_Teached_Bart_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_Bart_50k
+
+This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5590
+- Rouge1: 0.4909
+- Rouge2: 0.2303
+- Rougel: 0.3967
+- Rougelsum: 0.3965
+- Gen Len: 38.2287
+- Precision: 0.9063
+- Recall: 0.9187
+- F1: 0.9123
+
+## 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 | 1.6214 | 0.4804 | 0.2218 | 0.3873 | 0.3873 | 38.3549 | 0.9049 | 0.9166 | 0.9106 |
+| 1.5842 | 2.0 | 781 | 1.5548 | 0.4874 | 0.2283 | 0.3945 | 0.3945 | 37.8604 | 0.9059 | 0.9171 | 0.9113 |
+| 1.3014 | 3.0 | 1172 | 1.5461 | 0.49 | 0.2294 | 0.3975 | 0.3974 | 37.7564 | 0.9064 | 0.918 | 0.912 |
+| 1.18 | 3.99 | 1560 | 1.5590 | 0.4909 | 0.2303 | 0.3967 | 0.3965 | 38.2287 | 0.9063 | 0.9187 | 0.9123 |
+
+
+### 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": 2,
+ "early_stopping": true,
+ "eos_token_id": 2,
+ "forced_eos_token_id": 2,
+ "max_length": 62,
+ "min_length": 11,
+ "no_repeat_ngram_size": 3,
+ "num_beams": 6,
+ "pad_token_id": 1,
+ "transformers_version": "4.36.0"
+}

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