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joshcarp_-_gpt2-evy-gguf
RichardErkhov/joshcarp_-_gpt2-evy-gguf
joshcarp_-_gpt2-evy-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf2.2 GB · 100%
At a glance
- Access
- Public
- Created
- Nov 3, 2024
- Updated
- Nov 3, 2024
- SHA
- 7c2978dd
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
gpt2-evy - GGUF
- Model creator: https://huggingface.co/joshcarp/
- Original model: https://huggingface.co/joshcarp/gpt2-evy/
| Name | Quant method | Size |
|---|---|---|
| gpt2-evy.Q2_K.gguf | Q2_K | 0.08GB |
| gpt2-evy.Q3_K_S.gguf | Q3_K_S | 0.08GB |
| gpt2-evy.Q3_K.gguf | Q3_K | 0.09GB |
| gpt2-evy.Q3_K_M.gguf | Q3_K_M | 0.09GB |
| gpt2-evy.Q3_K_L.gguf | Q3_K_L | 0.1GB |
| gpt2-evy.IQ4_XS.gguf | IQ4_XS | 0.1GB |
| gpt2-evy.Q4_0.gguf | Q4_0 | 0.1GB |
| gpt2-evy.IQ4_NL.gguf | IQ4_NL | 0.1GB |
| gpt2-evy.Q4_K_S.gguf | Q4_K_S | 0.1GB |
| gpt2-evy.Q4_K.gguf | Q4_K | 0.11GB |
| gpt2-evy.Q4_K_M.gguf | Q4_K_M | 0.11GB |
| gpt2-evy.Q4_1.gguf | Q4_1 | 0.11GB |
| gpt2-evy.Q5_0.gguf | Q5_0 | 0.11GB |
| gpt2-evy.Q5_K_S.gguf | Q5_K_S | 0.11GB |
| gpt2-evy.Q5_K.gguf | Q5_K | 0.12GB |
| gpt2-evy.Q5_K_M.gguf | Q5_K_M | 0.12GB |
| gpt2-evy.Q5_1.gguf | Q5_1 | 0.12GB |
| gpt2-evy.Q6_K.gguf | Q6_K | 0.13GB |
| gpt2-evy.Q8_0.gguf | Q8_0 | 0.17GB |
Original model description:
license: mit tags:
- generated_from_trainer base_model: gpt2 model-index:
- name: gpt2-evy 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. -->
gpt2-evy
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5637
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: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 31 | 1.1270 |
| No log | 2.0 | 62 | 0.9170 |
| No log | 3.0 | 93 | 0.8410 |
| 1.3727 | 4.0 | 124 | 0.7949 |
| 1.3727 | 5.0 | 155 | 0.7361 |
| 1.3727 | 6.0 | 186 | 0.7021 |
| 0.9077 | 7.0 | 217 | 0.6789 |
| 0.9077 | 8.0 | 248 | 0.6490 |
| 0.9077 | 9.0 | 279 | 0.6346 |
| 0.7106 | 10.0 | 310 | 0.6219 |
| 0.7106 | 11.0 | 341 | 0.5986 |
| 0.7106 | 12.0 | 372 | 0.5797 |
| 0.5814 | 13.0 | 403 | 0.5835 |
| 0.5814 | 14.0 | 434 | 0.5872 |
| 0.5814 | 15.0 | 465 | 0.5741 |
| 0.5814 | 16.0 | 496 | 0.5749 |
| 0.4916 | 17.0 | 527 | 0.5662 |
| 0.4916 | 18.0 | 558 | 0.5529 |
| 0.4916 | 19.0 | 589 | 0.5672 |
| 0.4005 | 20.0 | 620 | 0.5646 |
| 0.4005 | 21.0 | 651 | 0.5701 |
| 0.4005 | 22.0 | 682 | 0.5650 |
| 0.357 | 23.0 | 713 | 0.5637 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Created
- Nov 3, 2024
- Updated
- Nov 3, 2024