Model save
Browse files- README.md +77 -0
- trainer_log.jsonl +28 -0
README.md
ADDED
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: gemma
|
3 |
+
library_name: peft
|
4 |
+
tags:
|
5 |
+
- trl
|
6 |
+
- dpo
|
7 |
+
- llama-factory
|
8 |
+
- generated_from_trainer
|
9 |
+
base_model: google/gemma-7b-it
|
10 |
+
model-index:
|
11 |
+
- name: Gemma-7B-It-ORPO-SALT-HALF
|
12 |
+
results: []
|
13 |
+
---
|
14 |
+
|
15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
16 |
+
should probably proofread and complete it, then remove this comment. -->
|
17 |
+
|
18 |
+
# Gemma-7B-It-ORPO-SALT-HALF
|
19 |
+
|
20 |
+
This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) on the None dataset.
|
21 |
+
It achieves the following results on the evaluation set:
|
22 |
+
- Loss: 1.3159
|
23 |
+
- Rewards/chosen: -0.1249
|
24 |
+
- Rewards/rejected: -0.1471
|
25 |
+
- Rewards/accuracies: 0.5619
|
26 |
+
- Rewards/margins: 0.0222
|
27 |
+
- Logps/rejected: -1.4709
|
28 |
+
- Logps/chosen: -1.2488
|
29 |
+
- Logits/rejected: 253.8645
|
30 |
+
- Logits/chosen: 253.5439
|
31 |
+
- Sft Loss: 1.2488
|
32 |
+
- Odds Ratio Loss: 0.6713
|
33 |
+
|
34 |
+
## Model description
|
35 |
+
|
36 |
+
More information needed
|
37 |
+
|
38 |
+
## Intended uses & limitations
|
39 |
+
|
40 |
+
More information needed
|
41 |
+
|
42 |
+
## Training and evaluation data
|
43 |
+
|
44 |
+
More information needed
|
45 |
+
|
46 |
+
## Training procedure
|
47 |
+
|
48 |
+
### Training hyperparameters
|
49 |
+
|
50 |
+
The following hyperparameters were used during training:
|
51 |
+
- learning_rate: 5e-06
|
52 |
+
- train_batch_size: 2
|
53 |
+
- eval_batch_size: 2
|
54 |
+
- seed: 42
|
55 |
+
- gradient_accumulation_steps: 8
|
56 |
+
- total_train_batch_size: 16
|
57 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
58 |
+
- lr_scheduler_type: cosine
|
59 |
+
- lr_scheduler_warmup_steps: 0.1
|
60 |
+
- num_epochs: 3.0
|
61 |
+
|
62 |
+
### Training results
|
63 |
+
|
64 |
+
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
|
65 |
+
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
|
66 |
+
| 1.422 | 0.8467 | 500 | 1.3896 | -0.1322 | -0.1546 | 0.5752 | 0.0224 | -1.5459 | -1.3222 | 250.5634 | 250.2739 | 1.3222 | 0.6733 |
|
67 |
+
| 1.3103 | 1.6935 | 1000 | 1.3313 | -0.1264 | -0.1489 | 0.5695 | 0.0224 | -1.4886 | -1.2642 | 253.1350 | 252.8147 | 1.2642 | 0.6718 |
|
68 |
+
| 1.2057 | 2.5402 | 1500 | 1.3159 | -0.1249 | -0.1471 | 0.5619 | 0.0222 | -1.4709 | -1.2488 | 253.8645 | 253.5439 | 1.2488 | 0.6713 |
|
69 |
+
|
70 |
+
|
71 |
+
### Framework versions
|
72 |
+
|
73 |
+
- PEFT 0.10.0
|
74 |
+
- Transformers 4.40.1
|
75 |
+
- Pytorch 2.3.0
|
76 |
+
- Datasets 2.19.0
|
77 |
+
- Tokenizers 0.19.1
|
trainer_log.jsonl
CHANGED
@@ -151,3 +151,31 @@
|
|
151 |
{"current_steps": 1490, "total_steps": 1770, "loss": 1.2608, "accuracy": 0.574999988079071, "learning_rate": 3.024615823368371e-07, "epoch": 2.523285351397121, "percentage": 84.18, "elapsed_time": "5:27:34", "remaining_time": "1:01:33"}
|
152 |
{"current_steps": 1500, "total_steps": 1770, "loss": 1.2057, "accuracy": 0.5625, "learning_rate": 2.8165102503600716e-07, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:29:42", "remaining_time": "0:59:20"}
|
153 |
{"current_steps": 1500, "total_steps": 1770, "eval_loss": 1.3159173727035522, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:33:24", "remaining_time": "1:00:00"}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
151 |
{"current_steps": 1490, "total_steps": 1770, "loss": 1.2608, "accuracy": 0.574999988079071, "learning_rate": 3.024615823368371e-07, "epoch": 2.523285351397121, "percentage": 84.18, "elapsed_time": "5:27:34", "remaining_time": "1:01:33"}
|
152 |
{"current_steps": 1500, "total_steps": 1770, "loss": 1.2057, "accuracy": 0.5625, "learning_rate": 2.8165102503600716e-07, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:29:42", "remaining_time": "0:59:20"}
|
153 |
{"current_steps": 1500, "total_steps": 1770, "eval_loss": 1.3159173727035522, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:33:24", "remaining_time": "1:00:00"}
|
154 |
+
{"current_steps": 1510, "total_steps": 1770, "loss": 1.3937, "accuracy": 0.543749988079071, "learning_rate": 2.615393769259039e-07, "epoch": 2.557154953429297, "percentage": 85.31, "elapsed_time": "5:35:40", "remaining_time": "0:57:47"}
|
155 |
+
{"current_steps": 1520, "total_steps": 1770, "loss": 1.2334, "accuracy": 0.543749988079071, "learning_rate": 2.421329743475917e-07, "epoch": 2.574089754445385, "percentage": 85.88, "elapsed_time": "5:37:46", "remaining_time": "0:55:33"}
|
156 |
+
{"current_steps": 1530, "total_steps": 1770, "loss": 1.3281, "accuracy": 0.5375000238418579, "learning_rate": 2.234379314486973e-07, "epoch": 2.5910245554614733, "percentage": 86.44, "elapsed_time": "5:39:57", "remaining_time": "0:53:19"}
|
157 |
+
{"current_steps": 1540, "total_steps": 1770, "loss": 1.2628, "accuracy": 0.6000000238418579, "learning_rate": 2.0546013825709783e-07, "epoch": 2.6079593564775614, "percentage": 87.01, "elapsed_time": "5:42:10", "remaining_time": "0:51:06"}
|
158 |
+
{"current_steps": 1550, "total_steps": 1770, "loss": 1.1414, "accuracy": 0.6187499761581421, "learning_rate": 1.88205258825217e-07, "epoch": 2.6248941574936495, "percentage": 87.57, "elapsed_time": "5:44:24", "remaining_time": "0:48:53"}
|
159 |
+
{"current_steps": 1560, "total_steps": 1770, "loss": 1.2452, "accuracy": 0.550000011920929, "learning_rate": 1.7167872944552245e-07, "epoch": 2.6418289585097376, "percentage": 88.14, "elapsed_time": "5:46:29", "remaining_time": "0:46:38"}
|
160 |
+
{"current_steps": 1570, "total_steps": 1770, "loss": 1.2281, "accuracy": 0.5, "learning_rate": 1.5588575693777142e-07, "epoch": 2.6587637595258258, "percentage": 88.7, "elapsed_time": "5:48:43", "remaining_time": "0:44:25"}
|
161 |
+
{"current_steps": 1580, "total_steps": 1770, "loss": 1.3435, "accuracy": 0.5062500238418579, "learning_rate": 1.4083131700856428e-07, "epoch": 2.675698560541914, "percentage": 89.27, "elapsed_time": "5:50:58", "remaining_time": "0:42:12"}
|
162 |
+
{"current_steps": 1590, "total_steps": 1770, "loss": 1.2371, "accuracy": 0.606249988079071, "learning_rate": 1.2652015268370315e-07, "epoch": 2.6926333615580016, "percentage": 89.83, "elapsed_time": "5:53:06", "remaining_time": "0:39:58"}
|
163 |
+
{"current_steps": 1600, "total_steps": 1770, "loss": 1.3777, "accuracy": 0.581250011920929, "learning_rate": 1.1295677281386502e-07, "epoch": 2.7095681625740897, "percentage": 90.4, "elapsed_time": "5:55:21", "remaining_time": "0:37:45"}
|
164 |
+
{"current_steps": 1610, "total_steps": 1770, "loss": 1.323, "accuracy": 0.574999988079071, "learning_rate": 1.0014545065404973e-07, "epoch": 2.726502963590178, "percentage": 90.96, "elapsed_time": "5:57:31", "remaining_time": "0:35:31"}
|
165 |
+
{"current_steps": 1620, "total_steps": 1770, "loss": 1.285, "accuracy": 0.574999988079071, "learning_rate": 8.809022251725502e-08, "epoch": 2.743437764606266, "percentage": 91.53, "elapsed_time": "5:59:42", "remaining_time": "0:33:18"}
|
166 |
+
{"current_steps": 1630, "total_steps": 1770, "loss": 1.3117, "accuracy": 0.5375000238418579, "learning_rate": 7.679488650280509e-08, "epoch": 2.7603725656223537, "percentage": 92.09, "elapsed_time": "6:01:57", "remaining_time": "0:31:05"}
|
167 |
+
{"current_steps": 1640, "total_steps": 1770, "loss": 1.2449, "accuracy": 0.5375000238418579, "learning_rate": 6.626300129972563e-08, "epoch": 2.777307366638442, "percentage": 92.66, "elapsed_time": "6:03:59", "remaining_time": "0:28:51"}
|
168 |
+
{"current_steps": 1650, "total_steps": 1770, "loss": 1.2878, "accuracy": 0.6000000238418579, "learning_rate": 5.649788506555065e-08, "epoch": 2.79424216765453, "percentage": 93.22, "elapsed_time": "6:06:05", "remaining_time": "0:26:37"}
|
169 |
+
{"current_steps": 1660, "total_steps": 1770, "loss": 1.2631, "accuracy": 0.581250011920929, "learning_rate": 4.7502614380908474e-08, "epoch": 2.811176968670618, "percentage": 93.79, "elapsed_time": "6:08:16", "remaining_time": "0:24:24"}
|
170 |
+
{"current_steps": 1670, "total_steps": 1770, "loss": 1.2531, "accuracy": 0.550000011920929, "learning_rate": 3.9280023280222066e-08, "epoch": 2.828111769686706, "percentage": 94.35, "elapsed_time": "6:10:25", "remaining_time": "0:22:10"}
|
171 |
+
{"current_steps": 1680, "total_steps": 1770, "loss": 1.288, "accuracy": 0.5562499761581421, "learning_rate": 3.1832702358818855e-08, "epoch": 2.8450465707027943, "percentage": 94.92, "elapsed_time": "6:12:45", "remaining_time": "0:19:58"}
|
172 |
+
{"current_steps": 1690, "total_steps": 1770, "loss": 1.2743, "accuracy": 0.5687500238418579, "learning_rate": 2.5162997956746647e-08, "epoch": 2.8619813717188824, "percentage": 95.48, "elapsed_time": "6:15:05", "remaining_time": "0:17:45"}
|
173 |
+
{"current_steps": 1700, "total_steps": 1770, "loss": 1.3412, "accuracy": 0.5874999761581421, "learning_rate": 1.9273011419536914e-08, "epoch": 2.8789161727349706, "percentage": 96.05, "elapsed_time": "6:17:00", "remaining_time": "0:15:31"}
|
174 |
+
{"current_steps": 1710, "total_steps": 1770, "loss": 1.2679, "accuracy": 0.5562499761581421, "learning_rate": 1.4164598436159083e-08, "epoch": 2.8958509737510583, "percentage": 96.61, "elapsed_time": "6:19:03", "remaining_time": "0:13:18"}
|
175 |
+
{"current_steps": 1720, "total_steps": 1770, "loss": 1.213, "accuracy": 0.606249988079071, "learning_rate": 9.839368454371556e-09, "epoch": 2.9127857747671464, "percentage": 97.18, "elapsed_time": "6:21:14", "remaining_time": "0:11:04"}
|
176 |
+
{"current_steps": 1730, "total_steps": 1770, "loss": 1.2129, "accuracy": 0.5874999761581421, "learning_rate": 6.298684173650649e-09, "epoch": 2.9297205757832345, "percentage": 97.74, "elapsed_time": "6:23:20", "remaining_time": "0:08:51"}
|
177 |
+
{"current_steps": 1740, "total_steps": 1770, "loss": 1.2883, "accuracy": 0.5625, "learning_rate": 3.543661115860686e-09, "epoch": 2.9466553767993227, "percentage": 98.31, "elapsed_time": "6:25:17", "remaining_time": "0:06:38"}
|
178 |
+
{"current_steps": 1750, "total_steps": 1770, "loss": 1.249, "accuracy": 0.574999988079071, "learning_rate": 1.575167273800693e-09, "epoch": 2.963590177815411, "percentage": 98.87, "elapsed_time": "6:27:15", "remaining_time": "0:04:25"}
|
179 |
+
{"current_steps": 1760, "total_steps": 1770, "loss": 1.3394, "accuracy": 0.574999988079071, "learning_rate": 3.9382283773564676e-10, "epoch": 2.9805249788314985, "percentage": 99.44, "elapsed_time": "6:29:28", "remaining_time": "0:02:12"}
|
180 |
+
{"current_steps": 1770, "total_steps": 1770, "loss": 1.3966, "accuracy": 0.606249988079071, "learning_rate": 0.0, "epoch": 2.9974597798475866, "percentage": 100.0, "elapsed_time": "6:31:33", "remaining_time": "0:00:00"}
|
181 |
+
{"current_steps": 1770, "total_steps": 1770, "epoch": 2.9974597798475866, "percentage": 100.0, "elapsed_time": "6:31:33", "remaining_time": "0:00:00"}
|