---
license: apache-2.0
base_model: DesilDev/Blocksmith
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: BlocksmithV2
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 39.0411
---

<!-- 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. -->

# BlocksmithV2

This model is a fine-tuned version of [DesilDev/Blocksmith](https://huggingface.co/DesilDev/Blocksmith) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8786
- Rouge1: 39.0411
- Rouge2: 16.2095
- Rougel: 32.6745
- Rougelsum: 35.9911
- Gen Len: 16.28

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.115         | 1.0   | 921  | 1.8786          | 39.0411 | 16.2095 | 32.6745 | 35.9911   | 16.28   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1