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silviasapora
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gemma-7b-orpo-low-quality

Text Generation
Transformers
TensorBoard
Safetensors
gemma
alignment-handbook
trl
orpo
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
Model card Files Metrics Community
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README.md CHANGED
@@ -5,6 +5,7 @@ base_model: google/gemma-7b
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  tags:
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  - trl
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  - orpo
 
8
  - generated_from_trainer
9
  model-index:
10
  - name: gemma-7b-orpo-low-quality
@@ -16,20 +17,20 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  # gemma-7b-orpo-low-quality
18
 
19
- This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the None dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 1.7140
22
- - Rewards/chosen: -0.0627
23
- - Rewards/rejected: -0.0713
24
- - Rewards/accuracies: 0.5468
25
- - Rewards/margins: 0.0086
26
- - Logps/rejected: -1.4256
27
- - Logps/chosen: -1.2543
28
- - Logits/rejected: 254.8359
29
- - Logits/chosen: 284.1839
30
- - Nll Loss: 1.6445
31
- - Log Odds Ratio: -0.7198
32
- - Log Odds Chosen: 0.2700
33
 
34
  ## Model description
35
 
@@ -49,13 +50,14 @@ More information needed
49
 
50
  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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- - train_batch_size: 1
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  - eval_batch_size: 1
54
  - seed: 42
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  - distributed_type: multi-GPU
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- - num_devices: 4
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- - total_train_batch_size: 4
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- - total_eval_batch_size: 4
 
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: inverse_sqrt
61
  - lr_scheduler_warmup_steps: 100
@@ -63,11 +65,11 @@ The following hyperparameters were used during training:
63
 
64
  ### Training results
65
 
66
- | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
67
- |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
68
- | 1.4383 | 1.0 | 1341 | 1.4377 | -0.0510 | -0.0574 | 0.5396 | 0.0064 | -1.1482 | -1.0204 | 305.7246 | 332.3974 | 1.3887 | -0.7026 | 0.2118 |
69
- | 0.7446 | 2.0 | 2682 | 1.4665 | -0.0520 | -0.0604 | 0.5180 | 0.0084 | -1.2083 | -1.0407 | 290.7071 | 318.0078 | 1.4117 | -0.6996 | 0.2745 |
70
- | 0.3228 | 3.0 | 4023 | 1.7140 | -0.0627 | -0.0713 | 0.5468 | 0.0086 | -1.4256 | -1.2543 | 254.8359 | 284.1839 | 1.6445 | -0.7198 | 0.2700 |
71
 
72
 
73
  ### Framework versions
 
5
  tags:
6
  - trl
7
  - orpo
8
+ - alignment-handbook
9
  - generated_from_trainer
10
  model-index:
11
  - name: gemma-7b-orpo-low-quality
 
17
 
18
  # gemma-7b-orpo-low-quality
19
 
20
+ This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 1.6395
23
+ - Rewards/chosen: -0.0601
24
+ - Rewards/rejected: -0.0755
25
+ - Rewards/accuracies: 0.6029
26
+ - Rewards/margins: 0.0153
27
+ - Logps/rejected: -1.5091
28
+ - Logps/chosen: -1.2026
29
+ - Logits/rejected: 275.9735
30
+ - Logits/chosen: 286.3763
31
+ - Nll Loss: 1.5847
32
+ - Log Odds Ratio: -0.6702
33
+ - Log Odds Chosen: 0.4438
34
 
35
  ## Model description
36
 
 
50
 
51
  The following hyperparameters were used during training:
52
  - learning_rate: 5e-06
53
+ - train_batch_size: 2
54
  - eval_batch_size: 1
55
  - seed: 42
56
  - distributed_type: multi-GPU
57
+ - num_devices: 2
58
+ - gradient_accumulation_steps: 8
59
+ - total_train_batch_size: 32
60
+ - total_eval_batch_size: 2
61
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
62
  - lr_scheduler_type: inverse_sqrt
63
  - lr_scheduler_warmup_steps: 100
 
65
 
66
  ### Training results
67
 
68
+ | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
69
+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
70
+ | 1.4933 | 0.9976 | 157 | 1.4686 | -0.0501 | -0.0608 | 0.5776 | 0.0107 | -1.2166 | -1.0023 | 307.1602 | 318.2524 | 1.4127 | -0.6558 | 0.3240 |
71
+ | 1.036 | 1.9952 | 314 | 1.4194 | -0.0493 | -0.0612 | 0.5668 | 0.0118 | -1.2231 | -0.9867 | 302.5974 | 312.9305 | 1.3670 | -0.6609 | 0.3487 |
72
+ | 0.56 | 2.9929 | 471 | 1.6395 | -0.0601 | -0.0755 | 0.6029 | 0.0153 | -1.5091 | -1.2026 | 275.9735 | 286.3763 | 1.5847 | -0.6702 | 0.4438 |
73
 
74
 
75
  ### Framework versions
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