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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: all_9843_bart-base
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. -->
# all_9843_bart-base
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: 1.2356
- Rouge1: 0.2722
- Rouge2: 0.1239
- Rougel: 0.2315
- Rougelsum: 0.2424
- Gen Len: 19.9567
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.759 | 0.89 | 500 | 1.2348 | 0.2615 | 0.1071 | 0.2187 | 0.2283 | 19.956 |
| 1.0891 | 1.78 | 1000 | 1.2122 | 0.2667 | 0.1145 | 0.224 | 0.2351 | 19.9713 |
| 0.9877 | 2.67 | 1500 | 1.2076 | 0.2701 | 0.118 | 0.2271 | 0.238 | 19.9413 |
| 0.9299 | 3.56 | 2000 | 1.2072 | 0.2682 | 0.1205 | 0.2267 | 0.2385 | 19.9667 |
| 0.8841 | 4.44 | 2500 | 1.2088 | 0.2711 | 0.1213 | 0.2294 | 0.2406 | 19.956 |
| 0.8425 | 5.33 | 3000 | 1.2154 | 0.2718 | 0.1245 | 0.2317 | 0.2426 | 19.9673 |
| 0.8123 | 6.22 | 3500 | 1.2276 | 0.2719 | 0.1242 | 0.2315 | 0.2422 | 19.958 |
| 0.7876 | 7.11 | 4000 | 1.2259 | 0.2726 | 0.1228 | 0.2311 | 0.242 | 19.9647 |
| 0.769 | 8.0 | 4500 | 1.2244 | 0.2733 | 0.126 | 0.2324 | 0.2436 | 19.9667 |
| 0.75 | 8.89 | 5000 | 1.2313 | 0.2723 | 0.1236 | 0.231 | 0.2422 | 19.964 |
| 0.7369 | 9.78 | 5500 | 1.2356 | 0.2722 | 0.1239 | 0.2315 | 0.2424 | 19.9567 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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