Instructions to use athirorg/USS-reward-model-grl-source with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use athirorg/USS-reward-model-grl-source with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("athirorg/USS-reward-model-grl-source") model = AutoModel.from_pretrained("athirorg/USS-reward-model-grl-source") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +75 -0
- model.safetensors +1 -1
README.md
ADDED
|
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: apache-2.0
|
| 4 |
+
base_model: answerdotai/ModernBERT-large
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
model-index:
|
| 8 |
+
- name: USS-reward-model-grl-source
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# USS-reward-model-grl-source
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 52.9809
|
| 20 |
+
- Mse: 0.1859
|
| 21 |
+
- Mae: 0.2835
|
| 22 |
+
- R2: 0.0363
|
| 23 |
+
- Spearman Correlation: 0.1418
|
| 24 |
+
|
| 25 |
+
## Model description
|
| 26 |
+
|
| 27 |
+
More information needed
|
| 28 |
+
|
| 29 |
+
## Intended uses & limitations
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Training and evaluation data
|
| 34 |
+
|
| 35 |
+
More information needed
|
| 36 |
+
|
| 37 |
+
## Training procedure
|
| 38 |
+
|
| 39 |
+
### Training hyperparameters
|
| 40 |
+
|
| 41 |
+
The following hyperparameters were used during training:
|
| 42 |
+
- learning_rate: 2e-05
|
| 43 |
+
- train_batch_size: 2
|
| 44 |
+
- eval_batch_size: 1
|
| 45 |
+
- seed: 42
|
| 46 |
+
- distributed_type: multi-GPU
|
| 47 |
+
- gradient_accumulation_steps: 10
|
| 48 |
+
- total_train_batch_size: 20
|
| 49 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 10
|
| 52 |
+
- mixed_precision_training: Native AMP
|
| 53 |
+
|
| 54 |
+
### Training results
|
| 55 |
+
|
| 56 |
+
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Spearman Correlation |
|
| 57 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------------------:|
|
| 58 |
+
| 22.9021 | 1.0 | 97 | 1.5700 | 0.1938 | 0.2856 | -0.0045 | nan |
|
| 59 |
+
| 17.8187 | 2.0 | 194 | 2.1893 | 0.2106 | 0.3009 | -0.0917 | 0.1105 |
|
| 60 |
+
| 290.6176 | 3.0 | 291 | 47.6834 | 0.5032 | 0.5697 | -1.6088 | 0.1146 |
|
| 61 |
+
| 518.1736 | 4.0 | 388 | 54.6556 | 0.2628 | 0.3755 | -0.3622 | 0.1508 |
|
| 62 |
+
| 567.3146 | 5.0 | 485 | 57.8539 | 0.3017 | 0.4718 | -0.5641 | 0.1994 |
|
| 63 |
+
| 574.1879 | 6.0 | 582 | 56.7874 | 0.2290 | 0.4001 | -0.1873 | 0.1062 |
|
| 64 |
+
| 559.3920 | 7.0 | 679 | 55.2139 | 0.2447 | 0.3755 | -0.2685 | 0.1472 |
|
| 65 |
+
| 544.8656 | 8.0 | 776 | 54.0387 | 0.2628 | 0.3924 | -0.3626 | 0.1332 |
|
| 66 |
+
| 535.0054 | 9.0 | 873 | 53.2574 | 0.2067 | 0.2983 | -0.0716 | 0.1215 |
|
| 67 |
+
| 529.6823 | 10.0 | 970 | 52.9809 | 0.1859 | 0.2835 | 0.0363 | 0.1418 |
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
### Framework versions
|
| 71 |
+
|
| 72 |
+
- Transformers 5.9.0
|
| 73 |
+
- Pytorch 2.12.0+cu130
|
| 74 |
+
- Datasets 4.8.5
|
| 75 |
+
- Tokenizers 0.22.2
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1583364164
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:febd21b4644fcd5625ec42fb0cb00774fbdcf374b924d54f834c96f50a0d4f0d
|
| 3 |
size 1583364164
|