Downloads · 30 days
24
9% of all-time downloads
distilgpt2-mentalchat16k
advy/distilgpt2-mentalchat16k
distilgpt2-mentalchat16k is a machine learning model from advy. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
277
Public
Repo size
111 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.json8.7 MB · 38%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Nov 16, 2025
- Updated
- Nov 16, 2025
- SHA
- 5232743b
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
distilgpt2-mentalchat16k
This model is a fine-tuned version of distilgpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7166
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch 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: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6182 | 0.1496 | 100 | 2.2105 |
| 2.2076 | 0.2992 | 200 | 2.0442 |
| 2.0966 | 0.4488 | 300 | 1.9762 |
| 2.0588 | 0.5984 | 400 | 1.9349 |
| 2.0266 | 0.7479 | 500 | 1.8990 |
| 1.9837 | 0.8975 | 600 | 1.8681 |
| 1.955 | 1.0471 | 700 | 1.8443 |
| 1.9298 | 1.1967 | 800 | 1.8224 |
| 1.9156 | 1.3463 | 900 | 1.8075 |
| 1.9128 | 1.4959 | 1000 | 1.7937 |
| 1.9054 | 1.6455 | 1100 | 1.7831 |
| 1.8468 | 1.7951 | 1200 | 1.7702 |
| 1.8663 | 1.9447 | 1300 | 1.7631 |
| 1.8413 | 2.0942 | 1400 | 1.7529 |
| 1.8356 | 2.2438 | 1500 | 1.7486 |
| 1.8324 | 2.3934 | 1600 | 1.7444 |
| 1.8652 | 2.5430 | 1700 | 1.7358 |
| 1.8409 | 2.6926 | 1800 | 1.7331 |
| 1.8162 | 2.8422 | 1900 | 1.7313 |
| 1.8211 | 2.9918 | 2000 | 1.7283 |
| 1.828 | 3.1414 | 2100 | 1.7262 |
| 1.8139 | 3.2909 | 2200 | 1.7247 |
| 1.8168 | 3.4405 | 2300 | 1.7251 |
| 1.8191 | 3.5901 | 2400 | 1.7246 |
| 1.8285 | 3.7397 | 2500 | 1.7235 |
| 1.8085 | 3.8893 | 2600 | 1.7237 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- peft
- License
- apache-2.0
- Created
- Nov 16, 2025
- Updated
- Nov 16, 2025