your_model_path

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/bart-base
+tags:
+- generated_from_trainer
+metrics:
+- sacrebleu
+- rouge
+model-index:
+- name: bart-base-finetuned-w-data-augm-4e-5
+  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. -->
+
+# bart-base-finetuned-w-data-augm-4e-5
+
+This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3985
+- Sacrebleu: 89.8136
+- Rouge1: 95.6369
+- Rouge2: 91.8617
+- Rougel: 94.6909
+- Rougelsum: 94.6811
+- Bertscore Precision: 0.9424
+- Bertscore Recall: 0.9374
+- Bertscore F1: 0.9399
+
+## 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: 4.4252514647201465e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|
+| 0.1107        | 1.0   | 761  | 0.2850          | 90.5237   | 96.15   | 92.6707 | 95.2684 | 95.2821   | 0.9487              | 0.9425           | 0.9456       |
+| 0.0435        | 2.0   | 1522 | 0.2695          | 91.4933   | 96.4613 | 93.4149 | 95.6712 | 95.6642   | 0.9515              | 0.9522           | 0.9518       |
+| 0.0421        | 3.0   | 2283 | 0.2579          | 91.4926   | 96.4713 | 93.2669 | 95.7036 | 95.7071   | 0.9522              | 0.9505           | 0.9513       |
+| 0.0233        | 4.0   | 3044 | 0.2717          | 91.8243   | 96.6369 | 93.443  | 95.8509 | 95.8593   | 0.9537              | 0.9521           | 0.9529       |
+| 0.0327        | 5.0   | 3805 | 0.2804          | 92.095    | 96.6849 | 93.7485 | 95.9279 | 95.9247   | 0.9551              | 0.9526           | 0.9538       |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

generation_config.json

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+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "forced_bos_token_id": 0,
+  "forced_eos_token_id": 2,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 4,
+  "pad_token_id": 1,
+  "transformers_version": "4.44.2"
+}