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---
base_model: TinyLlama/TinyLlama_v1.1
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: tinyllama_magiccoder_reverse
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_magiccoder_reverse
This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co./TinyLlama/TinyLlama_v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4617
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7988 | 0.0262 | 4 | 1.8569 |
| 1.6885 | 0.0523 | 8 | 1.6512 |
| 1.5697 | 0.0785 | 12 | 1.6180 |
| 1.501 | 0.1047 | 16 | 1.5781 |
| 1.5529 | 0.1308 | 20 | 1.5673 |
| 1.4779 | 0.1570 | 24 | 1.5470 |
| 1.4724 | 0.1832 | 28 | 1.5328 |
| 1.5236 | 0.2093 | 32 | 1.5227 |
| 1.4405 | 0.2355 | 36 | 1.5105 |
| 1.5416 | 0.2617 | 40 | 1.5137 |
| 1.4954 | 0.2878 | 44 | 1.5066 |
| 1.5539 | 0.3140 | 48 | 1.4984 |
| 1.5253 | 0.3401 | 52 | 1.4869 |
| 1.4786 | 0.3663 | 56 | 1.4841 |
| 1.5582 | 0.3925 | 60 | 1.4856 |
| 1.5277 | 0.4186 | 64 | 1.4862 |
| 1.4553 | 0.4448 | 68 | 1.4852 |
| 1.472 | 0.4710 | 72 | 1.4787 |
| 1.4282 | 0.4971 | 76 | 1.4765 |
| 1.5454 | 0.5233 | 80 | 1.4738 |
| 1.5619 | 0.5495 | 84 | 1.4789 |
| 1.4621 | 0.5756 | 88 | 1.4715 |
| 1.3989 | 0.6018 | 92 | 1.4703 |
| 1.3913 | 0.6280 | 96 | 1.4723 |
| 1.4797 | 0.6541 | 100 | 1.4636 |
| 1.4766 | 0.6803 | 104 | 1.4707 |
| 1.4478 | 0.7065 | 108 | 1.4650 |
| 1.4769 | 0.7326 | 112 | 1.4658 |
| 1.4517 | 0.7588 | 116 | 1.4650 |
| 1.4475 | 0.7850 | 120 | 1.4601 |
| 1.4842 | 0.8111 | 124 | 1.4645 |
| 1.4513 | 0.8373 | 128 | 1.4625 |
| 1.3405 | 0.8635 | 132 | 1.4614 |
| 1.5064 | 0.8896 | 136 | 1.4625 |
| 1.3767 | 0.9158 | 140 | 1.4628 |
| 1.429 | 0.9419 | 144 | 1.4623 |
| 1.4623 | 0.9681 | 148 | 1.4619 |
| 1.4592 | 0.9943 | 152 | 1.4617 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |