metadata
license: mit
base_model: croissantllm/CroissantCool-v0.2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llm2vec-croissant-mntp
results: []
llm2vec-croissant-mntp
This model is a fine-tuned version of croissantllm/CroissantCool-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8867
- Accuracy: 0.6078
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: 32
- 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 | 0.0884 | 100 | 4.7866 | 0.1990 |
| No log | 0.1768 | 200 | 4.0496 | 0.3309 |
| No log | 0.2653 | 300 | 3.6525 | 0.3779 |
| No log | 0.3537 | 400 | 3.2410 | 0.4258 |
| 3.9116 | 0.4421 | 500 | 3.6305 | 0.3912 |
| 3.9116 | 0.5305 | 600 | 3.1770 | 0.4406 |
| 3.9116 | 0.6189 | 700 | 2.4478 | 0.5199 |
| 3.9116 | 0.7073 | 800 | 2.2383 | 0.5508 |
| 3.9116 | 0.7958 | 900 | 2.1547 | 0.5635 |
| 2.4568 | 0.8842 | 1000 | 2.0868 | 0.5759 |
| 2.4568 | 0.9726 | 1100 | 2.0399 | 0.5820 |
| 2.4568 | 1.0610 | 1200 | 2.0102 | 0.5873 |
| 2.4568 | 1.1494 | 1300 | 1.9805 | 0.5897 |
| 2.4568 | 1.2378 | 1400 | 1.9590 | 0.5955 |
| 1.9305 | 1.3263 | 1500 | 1.9381 | 0.5982 |
| 1.9305 | 1.4147 | 1600 | 1.9249 | 0.5995 |
| 1.9305 | 1.5031 | 1700 | 1.9223 | 0.6017 |
| 1.9305 | 1.5915 | 1800 | 1.9091 | 0.6037 |
| 1.9305 | 1.6799 | 1900 | 1.9038 | 0.6042 |
| 1.8511 | 1.7683 | 2000 | 1.8982 | 0.6045 |
| 1.8511 | 1.8568 | 2100 | 1.8924 | 0.6060 |
| 1.8511 | 1.9452 | 2200 | 1.8844 | 0.6072 |
| 1.8511 | 2.0336 | 2300 | 1.8873 | 0.6087 |
| 1.8511 | 2.1220 | 2400 | 1.8889 | 0.6068 |
| 1.8197 | 2.2104 | 2500 | 1.8848 | 0.6080 |
| 1.8197 | 2.2989 | 2600 | 1.8736 | 0.6091 |
| 1.8197 | 2.3873 | 2700 | 1.8858 | 0.6072 |
| 1.8197 | 2.4757 | 2800 | 1.8814 | 0.6088 |
| 1.8197 | 2.5641 | 2900 | 1.8649 | 0.6103 |
| 1.8116 | 2.6525 | 3000 | 1.8647 | 0.6091 |
| 1.8116 | 2.7409 | 3100 | 1.8755 | 0.6101 |
| 1.8116 | 2.8294 | 3200 | 1.8755 | 0.6099 |
| 1.8116 | 2.9178 | 3300 | 1.8867 | 0.6078 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.0.1+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1