File size: 2,569 Bytes
7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d 7397806 d35901d |
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 |
---
library_name: peft
base_model: Anwaarma/edos_taskB_llama3b_merged2_FINAL
tags:
- base_model:adapter:Anwaarma/edos_taskB_llama3b_merged2_FINAL
- lora
- transformers
metrics:
- accuracy
model-index:
- name: try1
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. -->
# try1
This model is a fine-tuned version of [Anwaarma/edos_taskB_llama3b_merged2_FINAL](https://huggingface.co/Anwaarma/edos_taskB_llama3b_merged2_FINAL) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0008
- Accuracy: 0.6330
- F1 Macro: 0.5964
- F1 Micro: 0.6330
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 20
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.1785 | 1.8598 | 100 | 1.3641 | 0.5597 | 0.5106 | 0.5597 |
| 0.977 | 3.7103 | 200 | 1.2230 | 0.5905 | 0.5455 | 0.5905 |
| 0.833 | 5.5607 | 300 | 1.0872 | 0.6193 | 0.5723 | 0.6193 |
| 0.7542 | 7.4112 | 400 | 1.0395 | 0.6152 | 0.5523 | 0.6152 |
| 0.727 | 9.2617 | 500 | 0.9886 | 0.6502 | 0.5612 | 0.6502 |
| 0.7084 | 11.1121 | 600 | 0.9770 | 0.6523 | 0.5784 | 0.6523 |
| 0.7088 | 12.9720 | 700 | 0.9677 | 0.6502 | 0.5786 | 0.6502 |
| 0.7005 | 14.8224 | 800 | 0.9622 | 0.6523 | 0.5831 | 0.6523 |
| 0.6984 | 16.6729 | 900 | 0.9635 | 0.6543 | 0.5847 | 0.6543 |
| 0.6982 | 18.5234 | 1000 | 0.9632 | 0.6481 | 0.5721 | 0.6481 |
### Framework versions
- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.0 |