File size: 2,280 Bytes
0b09e6f 289332c 0b09e6f 289332c 0b09e6f 289332c 0b09e6f 289332c 0b09e6f |
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 80 81 82 83 |
---
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
model-index:
- name: llm2vec-qwen2.5-0.5-instruct
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: wikitext wikitext-103-raw-v1
type: wikitext
args: wikitext-103-raw-v1
metrics:
- name: Accuracy
type: accuracy
value: 0.629556877924779
---
<!-- 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. -->
# llm2vec-qwen2.5-0.5-instruct
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the wikitext wikitext-103-raw-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8264
- Accuracy: 0.6296
## 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: 16
- eval_batch_size: 32
- seed: 42
- 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 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0.0083 | 100 | 2.3376 | 0.5511 |
| No log | 0.0166 | 200 | 2.1736 | 0.5765 |
| No log | 0.0248 | 300 | 2.0679 | 0.5930 |
| No log | 0.0331 | 400 | 1.9839 | 0.6056 |
| 2.2761 | 0.0414 | 500 | 1.9611 | 0.6085 |
| 2.2761 | 0.0497 | 600 | 1.9054 | 0.6203 |
| 2.2761 | 0.0580 | 700 | 1.8838 | 0.6242 |
| 2.2761 | 0.0662 | 800 | 1.8403 | 0.6296 |
| 2.2761 | 0.0745 | 900 | 1.8235 | 0.6300 |
| 1.8887 | 0.0828 | 1000 | 1.7920 | 0.6351 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|