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lightblue_-_reranker_0.5_cont-gguf
RichardErkhov/lightblue_-_reranker_0.5_cont-gguf
lightblue_-_reranker_0.5_cont-gguf is a text ranking model from RichardErkhov. Use it for the text ranking task on the model card, and read the license before you ship it in a product.
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.gguf10.5 GB · 100%
At a glance
- Task
- Text Ranking
- Access
- Public
- Created
- Mar 14, 2025
- Updated
- Apr 2, 2025
- SHA
- 98997379
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
reranker_0.5_cont - GGUF
- Model creator: https://huggingface.co/lightblue/
- Original model: https://huggingface.co/lightblue/reranker_0.5_cont/
| Name | Quant method | Size |
|---|---|---|
| reranker_0.5_cont.Q2_K.gguf | Q2_K | 0.39GB |
| reranker_0.5_cont.IQ3_XS.gguf | IQ3_XS | 0.39GB |
| reranker_0.5_cont.IQ3_S.gguf | IQ3_S | 0.39GB |
| reranker_0.5_cont.Q3_K_S.gguf | Q3_K_S | 0.39GB |
| reranker_0.5_cont.IQ3_M.gguf | IQ3_M | 0.39GB |
| reranker_0.5_cont.Q3_K.gguf | Q3_K | 0.4GB |
| reranker_0.5_cont.Q3_K_M.gguf | Q3_K_M | 0.4GB |
| reranker_0.5_cont.Q3_K_L.gguf | Q3_K_L | 0.42GB |
| reranker_0.5_cont.IQ4_XS.gguf | IQ4_XS | 0.4GB |
| reranker_0.5_cont.Q4_0.gguf | Q4_0 | 0.4GB |
| reranker_0.5_cont.IQ4_NL.gguf | IQ4_NL | 0.4GB |
| reranker_0.5_cont.Q4_K_S.gguf | Q4_K_S | 0.45GB |
| reranker_0.5_cont.Q4_K.gguf | Q4_K | 0.46GB |
| reranker_0.5_cont.Q4_K_M.gguf | Q4_K_M | 0.46GB |
| reranker_0.5_cont.Q4_1.gguf | Q4_1 | 0.43GB |
| reranker_0.5_cont.Q5_0.gguf | Q5_0 | 0.46GB |
| reranker_0.5_cont.Q5_K_S.gguf | Q5_K_S | 0.48GB |
| reranker_0.5_cont.Q5_K.gguf | Q5_K | 0.49GB |
| reranker_0.5_cont.Q5_K_M.gguf | Q5_K_M | 0.49GB |
| reranker_0.5_cont.Q5_1.gguf | Q5_1 | 0.49GB |
| reranker_0.5_cont.Q6_K.gguf | Q6_K | 0.61GB |
| reranker_0.5_cont.Q8_0.gguf | Q8_0 | 0.63GB |
Original model description:
library_name: transformers license: other base_model: Qwen/Qwen2.5-0.5B-Instruct tags:
- llama-factory
- full
- generated_from_trainer model-index:
- name: reranker_continuous_train 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. -->
reranker_continuous_train
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the reranker_continuous_train dataset. It achieves the following results on the evaluation set:
- Loss: 0.3195
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_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: 0.01
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4242 | 0.1 | 2156 | 0.3844 |
| 0.236 | 0.2 | 4312 | 0.3643 |
| 0.6602 | 0.3 | 6468 | 0.3521 |
| 0.3464 | 0.4 | 8624 | 0.3472 |
| 0.3598 | 0.5 | 10780 | 0.3412 |
| 0.3377 | 0.6 | 12936 | 0.3341 |
| 0.4547 | 0.7 | 15092 | 0.3258 |
| 0.2282 | 0.8 | 17248 | 0.3228 |
| 0.2692 | 0.9 | 19404 | 0.3195 |
| 0.2059 | 1.0 | 21560 | 0.3195 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Ranking
- Created
- Mar 14, 2025
- Updated
- Apr 2, 2025