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abemorcal_-_ft_clm_eli5-gguf
RichardErkhov/abemorcal_-_ft_clm_eli5-gguf
abemorcal_-_ft_clm_eli5-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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At a glance
- Access
- Public
- Created
- Feb 11, 2025
- Updated
- Feb 12, 2025
- SHA
- 918188df
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
ft_clm_eli5 - GGUF
- Model creator: https://huggingface.co/abemorcal/
- Original model: https://huggingface.co/abemorcal/ft_clm_eli5/
| Name | Quant method | Size |
|---|---|---|
| ft_clm_eli5.Q2_K.gguf | Q2_K | 0.06GB |
| ft_clm_eli5.IQ3_XS.gguf | IQ3_XS | 0.07GB |
| ft_clm_eli5.IQ3_S.gguf | IQ3_S | 0.07GB |
| ft_clm_eli5.Q3_K_S.gguf | Q3_K_S | 0.07GB |
| ft_clm_eli5.IQ3_M.gguf | IQ3_M | 0.07GB |
| ft_clm_eli5.Q3_K.gguf | Q3_K | 0.07GB |
| ft_clm_eli5.Q3_K_M.gguf | Q3_K_M | 0.07GB |
| ft_clm_eli5.Q3_K_L.gguf | Q3_K_L | 0.07GB |
| ft_clm_eli5.IQ4_XS.gguf | IQ4_XS | 0.07GB |
| ft_clm_eli5.Q4_0.gguf | Q4_0 | 0.08GB |
| ft_clm_eli5.IQ4_NL.gguf | IQ4_NL | 0.08GB |
| ft_clm_eli5.Q4_K_S.gguf | Q4_K_S | 0.08GB |
| ft_clm_eli5.Q4_K.gguf | Q4_K | 0.08GB |
| ft_clm_eli5.Q4_K_M.gguf | Q4_K_M | 0.08GB |
| ft_clm_eli5.Q4_1.gguf | Q4_1 | 0.08GB |
| ft_clm_eli5.Q5_0.gguf | Q5_0 | 0.09GB |
| ft_clm_eli5.Q5_K_S.gguf | Q5_K_S | 0.09GB |
| ft_clm_eli5.Q5_K.gguf | Q5_K | 0.09GB |
| ft_clm_eli5.Q5_K_M.gguf | Q5_K_M | 0.09GB |
| ft_clm_eli5.Q5_1.gguf | Q5_1 | 0.09GB |
| ft_clm_eli5.Q6_K.gguf | Q6_K | 0.1GB |
| ft_clm_eli5.Q8_0.gguf | Q8_0 | 0.12GB |
Original model description:
library_name: transformers license: apache-2.0 base_model: distilbert/distilgpt2 tags:
- generated_from_trainer datasets:
- eli5_category model-index:
- name: ft_clm_eli5 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. -->
ft_clm_eli5
This model is a fine-tuned version of distilbert/distilgpt2 on the eli5_category dataset. It achieves the following results on the evaluation set:
- Loss: 3.8191
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.9502 | 1.0 | 1296 | 3.8309 |
| 3.8582 | 2.0 | 2592 | 3.8198 |
| 3.8206 | 3.0 | 3888 | 3.8191 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Created
- Feb 11, 2025
- Updated
- Feb 12, 2025