File size: 2,757 Bytes
f6358b9 7fd3737 f6358b9 0ac4467 f6358b9 0ac4467 f6358b9 49474e2 f6358b9 0ac4467 f6358b9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
library_name: peft
base_model: mjschock/TinyLlama-1.1B-Chat-v1.0
tags:
- trl
- sft
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: TinyLlama-1.1B-Chat-v1.0-sft-chat_threads
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. -->
# TinyLlama-1.1B-Chat-v1.0-sft-chat_threads
This model is a fine-tuned version of [mjschock/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co./mjschock/TinyLlama-1.1B-Chat-v1.0) on the mjschock/chat_threads dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5586
- Bleu: 0.7572
- Precisions: 0.7641
- Brevity Penalty: 0.9983
- Length Ratio: 0.9986
- Translation Length: 582.3552
- Reference Length: 582.9104
- Meteor: 0.7364
- Rouge1: 0.7900
- Rouge2: 0.5570
- Rougel: 0.7250
- Rougelsum: 0.7838
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Meteor | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|:------:|:------:|:---------:|
| No log | 0 | 0 | 0.8976 | 0.6391 | 0.6567 | 0.9934 | 0.9936 | 579.7720 | 582.9104 | 0.6775 | 0.6912 | 0.3881 | 0.5809 | 0.6813 |
| 0.7612 | 0.9630 | 13 | 0.7168 | 0.6941 | 0.7056 | 0.9969 | 0.9973 | 581.2681 | 582.9104 | 0.7030 | 0.7375 | 0.4604 | 0.6572 | 0.7281 |
| 0.6321 | 2.0 | 27 | 0.5992 | 0.7420 | 0.7498 | 0.9981 | 0.9981 | 582.0161 | 582.9104 | 0.7312 | 0.7780 | 0.5342 | 0.7069 | 0.7720 |
| 0.5738 | 2.8889 | 39 | 0.5586 | 0.7572 | 0.7641 | 0.9983 | 0.9986 | 582.3552 | 582.9104 | 0.7364 | 0.7900 | 0.5570 | 0.7250 | 0.7838 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1 |