transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-large-xsum base_model:finetune:facebook/bart-large-xsum license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-large-xsum
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: tech-dialogue-summarization
  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. -->

# tech-dialogue-summarization

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: 2.2347
- Rouge1: 28.5714
- Rouge2: 9.8361
- Rougel: 19.0476
- Rougelsum: 25.3968
- Gen Len: 21.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 1    | 2.5010          | 25.3968 | 9.8361 | 22.2222 | 25.3968   | 21.0    |
| No log        | 2.0   | 2    | 2.5010          | 25.3968 | 9.8361 | 22.2222 | 25.3968   | 21.0    |
| No log        | 3.0   | 3    | 2.2347          | 28.5714 | 9.8361 | 19.0476 | 25.3968   | 21.0    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
