---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_Bart_From_Scratch
  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_From_Scratch

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6350
- Rouge1: 0.4471
- Rouge2: 0.2259
- Rougel: 0.3846
- Rougelsum: 0.3845
- Gen Len: 19.9087
- Precision: 0.9156
- Recall: 0.8915
- F1: 0.9033

## 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: 24
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | F1     | Gen Len | Validation Loss | Precision | Recall | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:------:|:-------:|:---------------:|:---------:|:------:|:------:|:------:|:------:|:---------:|
| 1.836         | 1.0   | 521   | 0.8971 | 19.9745 | 1.5560          | 0.9105    | 0.8843 | 0.4155 | 0.2028 | 0.3561 | 0.3559    |
| 1.5951        | 2.0   | 1042  | 0.8997 | 19.9353 | 1.5004          | 0.9115    | 0.8886 | 0.4333 | 0.2136 | 0.3695 | 0.3694    |
| 1.469         | 3.0   | 1563  | 0.9001 | 19.9385 | 1.4691          | 0.912     | 0.8888 | 0.4355 | 0.2176 | 0.3729 | 0.3728    |
| 1.373         | 4.0   | 2084  | 0.9003 | 19.9647 | 1.4658          | 0.9137    | 0.8877 | 0.4311 | 0.2164 | 0.3706 | 0.3704    |
| 1.2902        | 5.0   | 2605  | 0.9008 | 19.9498 | 1.4542          | 0.9136    | 0.8887 | 0.4368 | 0.2218 | 0.3762 | 0.376     |
| 1.222         | 6.0   | 3126  | 0.9018 | 19.9425 | 1.4584          | 0.914     | 0.8902 | 0.4407 | 0.223  | 0.3802 | 0.3798    |
| 1.1655        | 7.0   | 3647  | 0.9019 | 19.9327 | 1.4709          | 0.9145    | 0.89   | 0.4404 | 0.2246 | 0.3806 | 0.3803    |
| 1.11          | 8.0   | 4168  | 0.9026 | 19.9084 | 1.4724          | 0.9153    | 0.8906 | 0.4435 | 0.2269 | 0.383  | 0.3828    |
| 1.0629        | 9.0   | 4689  | 0.9028 | 19.928  | 1.4853          | 0.9155    | 0.8908 | 0.4431 | 0.2273 | 0.3832 | 0.383     |
| 1.023         | 10.0  | 5210  | 0.9021 | 19.944  | 1.5033          | 0.9152    | 0.8897 | 0.4409 | 0.2247 | 0.3819 | 0.3818    |
| 0.9862        | 11.0  | 5731  | 0.9034 | 19.9124 | 1.5074          | 0.9158    | 0.8916 | 0.4479 | 0.2278 | 0.3862 | 0.386     |
| 0.957         | 12.0  | 6252  | 0.903  | 19.9033 | 1.5184          | 0.9159    | 0.8909 | 0.4461 | 0.2264 | 0.3846 | 0.3847    |
| 0.9315        | 13.0  | 6773  | 0.9031 | 19.9084 | 1.5269          | 0.9156    | 0.8912 | 0.4473 | 0.2284 | 0.386  | 0.3858    |
| 0.9093        | 14.0  | 7294  | 0.9029 | 19.9135 | 1.5311          | 0.9155    | 0.8909 | 0.4453 | 0.2273 | 0.3846 | 0.3843    |
| 0.8927        | 15.0  | 7815  | 0.9029 | 19.9065 | 1.5351          | 0.9156    | 0.8909 | 0.4457 | 0.2267 | 0.3842 | 0.384     |
| 0.8773        | 16.0  | 8336  | 0.9025 | 19.9425 | 1.5440          | 0.9151    | 0.8905 | 0.4427 | 0.225  | 0.382  | 0.382     |
| 0.8806        | 17.0  | 8857  | 0.9036 | 19.8851 | 1.5510          | 0.9159    | 0.8919 | 0.4495 | 0.2279 | 0.3868 | 0.3869    |
| 0.8683        | 18.0  | 9378  | 0.9038 | 19.8829 | 1.5679          | 0.9161    | 0.8921 | 0.4473 | 0.2282 | 0.3856 | 0.3857    |
| 0.8413        | 19.0  | 9899  | 0.9035 | 19.9135 | 1.5745          | 0.9159    | 0.8918 | 0.4492 | 0.2282 | 0.3861 | 0.3864    |
| 0.8257        | 20.0  | 10420 | 0.9031 | 19.8996 | 1.5835          | 0.9153    | 0.8915 | 0.4471 | 0.2266 | 0.3852 | 0.3853    |
| 0.8097        | 21.0  | 10941 | 0.9034 | 19.9073 | 1.5957          | 0.9156    | 0.8919 | 0.4472 | 0.2271 | 0.3856 | 0.3856    |
| 0.7926        | 22.0  | 11462 | 0.9034 | 19.892  | 1.5956          | 0.9159    | 0.8916 | 0.4479 | 0.2282 | 0.3855 | 0.3857    |
| 0.7841        | 23.0  | 11983 | 0.9028 | 19.912  | 1.5990          | 0.9155    | 0.8908 | 0.4444 | 0.2261 | 0.3833 | 0.3834    |
| 0.7669        | 24.0  | 12504 | 1.6097 | 0.4491  | 0.2284          | 0.3872    | 0.387  | 19.9007| 0.9162 | 0.892  | 0.9037    |
| 0.7733        | 25.0  | 13025 | 1.6060 | 0.4442  | 0.2257          | 0.3827    | 0.3828 | 19.9178| 0.9154 | 0.8906 | 0.9027    |
| 0.7631        | 26.0  | 13546 | 1.6187 | 0.4472  | 0.2276          | 0.3861    | 0.3861 | 19.9175| 0.9154 | 0.8915 | 0.9031    |
| 0.7505        | 27.0  | 14067 | 1.6208 | 0.4463  | 0.227           | 0.3852    | 0.3851 | 19.8967| 0.9155 | 0.8914 | 0.9031    |
| 0.7413        | 28.0  | 14588 | 1.6237 | 0.4468  | 0.2273          | 0.3854    | 0.3853 | 19.9153| 0.9159 | 0.8912 | 0.9032    |
| 0.7348        | 29.0  | 15109 | 1.6312 | 0.4482  | 0.2268          | 0.3858    | 0.3858 | 19.8938| 0.9158 | 0.8918 | 0.9035    |
| 0.7286        | 30.0  | 15630 | 1.6350 | 0.4471  | 0.2259          | 0.3846    | 0.3845 | 19.9087| 0.9156 | 0.8915 | 0.9033    |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0