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---
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
tags:
- summarization
- generated_from_trainer
model-index:
- name: TinyLlama-1.1B-Sum-SFT
results: []
datasets:
- martimfasantos/openai-summarize-tldr
pipeline_tag: summarization
---
<!-- 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. -->
# TinyLlama-1.1B-Sum-SFT
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the martimfasantos/openai-summarize-tldr dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8887
- Nll Loss: 1.8968
- Logps/best: -71.1814
- Rewards/chosen: 2.2080
- Rewards/rejected: -0.6886
- Rewards/accuracies: 1.0
- Rewards/margins: 2.8966
- Logps/rejected: -14.2972
- Logps/chosen: -71.1814
- Logits/rejected: -3.0553
- Logits/chosen: -3.4224
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Nll Loss | Logps/best | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.9469 | 0.2193 | 800 | 1.9582 | 1.9648 | -73.7246 | 1.9537 | -0.4240 | 1.0 | 2.3777 | -11.6512 | -73.7246 | -2.7987 | -3.1275 |
| 1.9813 | 0.4386 | 1600 | 1.9285 | 1.9369 | -72.6769 | 2.0585 | -0.5023 | 1.0 | 2.5607 | -12.4339 | -72.6769 | -2.9393 | -3.2910 |
| 1.9215 | 0.6579 | 2400 | 1.9049 | 1.9127 | -71.7733 | 2.1488 | -0.5719 | 1.0 | 2.7207 | -13.1300 | -71.7733 | -3.0198 | -3.3812 |
| 1.8655 | 0.8772 | 3200 | 1.8887 | 1.8968 | -71.1814 | 2.2080 | -0.6886 | 1.0 | 2.8966 | -14.2972 | -71.1814 | -3.0553 | -3.4224 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |