Upload 14 files
Browse files- README.md +37 -180
- adapter_model.safetensors +1 -1
- trainer_state.json +103 -3
README.md
CHANGED
@@ -1,202 +1,59 @@
|
|
1 |
---
|
|
|
2 |
library_name: peft
|
|
|
|
|
|
|
|
|
3 |
base_model: huggyllama/llama-7b
|
|
|
|
|
|
|
4 |
---
|
5 |
|
6 |
-
|
|
|
7 |
|
8 |
-
|
9 |
|
|
|
10 |
|
|
|
11 |
|
12 |
-
|
13 |
|
14 |
-
|
15 |
|
16 |
-
|
17 |
|
|
|
18 |
|
|
|
19 |
|
20 |
-
|
21 |
-
- **Funded by [optional]:** [More Information Needed]
|
22 |
-
- **Shared by [optional]:** [More Information Needed]
|
23 |
-
- **Model type:** [More Information Needed]
|
24 |
-
- **Language(s) (NLP):** [More Information Needed]
|
25 |
-
- **License:** [More Information Needed]
|
26 |
-
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
|
28 |
-
###
|
29 |
|
30 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
31 |
|
32 |
-
|
33 |
-
- **Paper [optional]:** [More Information Needed]
|
34 |
-
- **Demo [optional]:** [More Information Needed]
|
35 |
|
36 |
-
## Uses
|
37 |
|
38 |
-
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
|
40 |
-
### Direct Use
|
41 |
-
|
42 |
-
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
-
|
44 |
-
[More Information Needed]
|
45 |
-
|
46 |
-
### Downstream Use [optional]
|
47 |
-
|
48 |
-
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
-
|
50 |
-
[More Information Needed]
|
51 |
-
|
52 |
-
### Out-of-Scope Use
|
53 |
-
|
54 |
-
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
-
|
56 |
-
[More Information Needed]
|
57 |
-
|
58 |
-
## Bias, Risks, and Limitations
|
59 |
-
|
60 |
-
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
-
|
62 |
-
[More Information Needed]
|
63 |
-
|
64 |
-
### Recommendations
|
65 |
-
|
66 |
-
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
-
|
68 |
-
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
-
|
70 |
-
## How to Get Started with the Model
|
71 |
-
|
72 |
-
Use the code below to get started with the model.
|
73 |
-
|
74 |
-
[More Information Needed]
|
75 |
-
|
76 |
-
## Training Details
|
77 |
-
|
78 |
-
### Training Data
|
79 |
-
|
80 |
-
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
-
|
82 |
-
[More Information Needed]
|
83 |
-
|
84 |
-
### Training Procedure
|
85 |
-
|
86 |
-
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
-
|
88 |
-
#### Preprocessing [optional]
|
89 |
-
|
90 |
-
[More Information Needed]
|
91 |
-
|
92 |
-
|
93 |
-
#### Training Hyperparameters
|
94 |
-
|
95 |
-
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
-
|
97 |
-
#### Speeds, Sizes, Times [optional]
|
98 |
-
|
99 |
-
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
-
|
101 |
-
[More Information Needed]
|
102 |
-
|
103 |
-
## Evaluation
|
104 |
-
|
105 |
-
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
-
|
107 |
-
### Testing Data, Factors & Metrics
|
108 |
-
|
109 |
-
#### Testing Data
|
110 |
-
|
111 |
-
<!-- This should link to a Dataset Card if possible. -->
|
112 |
-
|
113 |
-
[More Information Needed]
|
114 |
-
|
115 |
-
#### Factors
|
116 |
-
|
117 |
-
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
-
|
119 |
-
[More Information Needed]
|
120 |
-
|
121 |
-
#### Metrics
|
122 |
-
|
123 |
-
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
-
|
125 |
-
[More Information Needed]
|
126 |
-
|
127 |
-
### Results
|
128 |
-
|
129 |
-
[More Information Needed]
|
130 |
-
|
131 |
-
#### Summary
|
132 |
-
|
133 |
-
|
134 |
-
|
135 |
-
## Model Examination [optional]
|
136 |
-
|
137 |
-
<!-- Relevant interpretability work for the model goes here -->
|
138 |
-
|
139 |
-
[More Information Needed]
|
140 |
-
|
141 |
-
## Environmental Impact
|
142 |
-
|
143 |
-
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
-
|
145 |
-
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
-
|
147 |
-
- **Hardware Type:** [More Information Needed]
|
148 |
-
- **Hours used:** [More Information Needed]
|
149 |
-
- **Cloud Provider:** [More Information Needed]
|
150 |
-
- **Compute Region:** [More Information Needed]
|
151 |
-
- **Carbon Emitted:** [More Information Needed]
|
152 |
-
|
153 |
-
## Technical Specifications [optional]
|
154 |
-
|
155 |
-
### Model Architecture and Objective
|
156 |
-
|
157 |
-
[More Information Needed]
|
158 |
-
|
159 |
-
### Compute Infrastructure
|
160 |
-
|
161 |
-
[More Information Needed]
|
162 |
-
|
163 |
-
#### Hardware
|
164 |
-
|
165 |
-
[More Information Needed]
|
166 |
-
|
167 |
-
#### Software
|
168 |
-
|
169 |
-
[More Information Needed]
|
170 |
-
|
171 |
-
## Citation [optional]
|
172 |
-
|
173 |
-
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
-
|
175 |
-
**BibTeX:**
|
176 |
-
|
177 |
-
[More Information Needed]
|
178 |
-
|
179 |
-
**APA:**
|
180 |
-
|
181 |
-
[More Information Needed]
|
182 |
-
|
183 |
-
## Glossary [optional]
|
184 |
-
|
185 |
-
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
-
|
187 |
-
[More Information Needed]
|
188 |
-
|
189 |
-
## More Information [optional]
|
190 |
-
|
191 |
-
[More Information Needed]
|
192 |
-
|
193 |
-
## Model Card Authors [optional]
|
194 |
-
|
195 |
-
[More Information Needed]
|
196 |
-
|
197 |
-
## Model Card Contact
|
198 |
-
|
199 |
-
[More Information Needed]
|
200 |
### Framework versions
|
201 |
|
202 |
-
- PEFT 0.10.0
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
+
license: other
|
3 |
library_name: peft
|
4 |
+
tags:
|
5 |
+
- llama-factory
|
6 |
+
- lora
|
7 |
+
- generated_from_trainer
|
8 |
base_model: huggyllama/llama-7b
|
9 |
+
model-index:
|
10 |
+
- name: custom1
|
11 |
+
results: []
|
12 |
---
|
13 |
|
14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
15 |
+
should probably proofread and complete it, then remove this comment. -->
|
16 |
|
17 |
+
# custom1
|
18 |
|
19 |
+
This model is a fine-tuned version of [huggyllama/llama-7b](https://huggingface.co/huggyllama/llama-7b) on the identity dataset.
|
20 |
|
21 |
+
## Model description
|
22 |
|
23 |
+
More information needed
|
24 |
|
25 |
+
## Intended uses & limitations
|
26 |
|
27 |
+
More information needed
|
28 |
|
29 |
+
## Training and evaluation data
|
30 |
|
31 |
+
More information needed
|
32 |
|
33 |
+
## Training procedure
|
|
|
|
|
|
|
|
|
|
|
|
|
34 |
|
35 |
+
### Training hyperparameters
|
36 |
|
37 |
+
The following hyperparameters were used during training:
|
38 |
+
- learning_rate: 5e-05
|
39 |
+
- train_batch_size: 2
|
40 |
+
- eval_batch_size: 8
|
41 |
+
- seed: 42
|
42 |
+
- gradient_accumulation_steps: 8
|
43 |
+
- total_train_batch_size: 16
|
44 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
45 |
+
- lr_scheduler_type: cosine
|
46 |
+
- num_epochs: 3.0
|
47 |
+
- mixed_precision_training: Native AMP
|
48 |
|
49 |
+
### Training results
|
|
|
|
|
50 |
|
|
|
51 |
|
|
|
52 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
53 |
### Framework versions
|
54 |
|
55 |
+
- PEFT 0.10.0
|
56 |
+
- Transformers 4.40.1
|
57 |
+
- Pytorch 2.2.1+cu121
|
58 |
+
- Datasets 2.19.0
|
59 |
+
- Tokenizers 0.19.1
|
adapter_model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 16794200
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d754527c09091f5c684d740413ac5fda645f387b868be523e3787f15e614ea73
|
3 |
size 16794200
|
trainer_state.json
CHANGED
@@ -1,9 +1,9 @@
|
|
1 |
{
|
2 |
"best_metric": null,
|
3 |
"best_model_checkpoint": null,
|
4 |
-
"epoch": 2.
|
5 |
"eval_steps": 500,
|
6 |
-
"global_step":
|
7 |
"is_hyper_param_search": false,
|
8 |
"is_local_process_zero": true,
|
9 |
"is_world_process_zero": true,
|
@@ -1687,6 +1687,106 @@
|
|
1687 |
"learning_rate": 3.345485990286029e-07,
|
1688 |
"loss": 1.9999,
|
1689 |
"step": 1200
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1690 |
}
|
1691 |
],
|
1692 |
"logging_steps": 5,
|
@@ -1694,7 +1794,7 @@
|
|
1694 |
"num_input_tokens_seen": 0,
|
1695 |
"num_train_epochs": 3,
|
1696 |
"save_steps": 100,
|
1697 |
-
"total_flos":
|
1698 |
"train_batch_size": 2,
|
1699 |
"trial_name": null,
|
1700 |
"trial_params": null
|
|
|
1 |
{
|
2 |
"best_metric": null,
|
3 |
"best_model_checkpoint": null,
|
4 |
+
"epoch": 2.9982238010657194,
|
5 |
"eval_steps": 500,
|
6 |
+
"global_step": 1266,
|
7 |
"is_hyper_param_search": false,
|
8 |
"is_local_process_zero": true,
|
9 |
"is_world_process_zero": true,
|
|
|
1687 |
"learning_rate": 3.345485990286029e-07,
|
1688 |
"loss": 1.9999,
|
1689 |
"step": 1200
|
1690 |
+
},
|
1691 |
+
{
|
1692 |
+
"epoch": 2.8537596210775606,
|
1693 |
+
"grad_norm": 1.529491901397705,
|
1694 |
+
"learning_rate": 2.8587263868213585e-07,
|
1695 |
+
"loss": 2.1399,
|
1696 |
+
"step": 1205
|
1697 |
+
},
|
1698 |
+
{
|
1699 |
+
"epoch": 2.865600947306098,
|
1700 |
+
"grad_norm": 1.5479165315628052,
|
1701 |
+
"learning_rate": 2.410013050375859e-07,
|
1702 |
+
"loss": 1.8664,
|
1703 |
+
"step": 1210
|
1704 |
+
},
|
1705 |
+
{
|
1706 |
+
"epoch": 2.877442273534636,
|
1707 |
+
"grad_norm": 1.1747933626174927,
|
1708 |
+
"learning_rate": 1.999415058312276e-07,
|
1709 |
+
"loss": 1.9633,
|
1710 |
+
"step": 1215
|
1711 |
+
},
|
1712 |
+
{
|
1713 |
+
"epoch": 2.8892835997631736,
|
1714 |
+
"grad_norm": 1.358820915222168,
|
1715 |
+
"learning_rate": 1.6269956203107117e-07,
|
1716 |
+
"loss": 2.0106,
|
1717 |
+
"step": 1220
|
1718 |
+
},
|
1719 |
+
{
|
1720 |
+
"epoch": 2.901124925991711,
|
1721 |
+
"grad_norm": 1.554287314414978,
|
1722 |
+
"learning_rate": 1.2928120686377388e-07,
|
1723 |
+
"loss": 1.7896,
|
1724 |
+
"step": 1225
|
1725 |
+
},
|
1726 |
+
{
|
1727 |
+
"epoch": 2.9129662522202486,
|
1728 |
+
"grad_norm": 1.5915781259536743,
|
1729 |
+
"learning_rate": 9.969158493204067e-08,
|
1730 |
+
"loss": 1.8759,
|
1731 |
+
"step": 1230
|
1732 |
+
},
|
1733 |
+
{
|
1734 |
+
"epoch": 2.924807578448786,
|
1735 |
+
"grad_norm": 1.6586300134658813,
|
1736 |
+
"learning_rate": 7.393525142262991e-08,
|
1737 |
+
"loss": 1.9413,
|
1738 |
+
"step": 1235
|
1739 |
+
},
|
1740 |
+
{
|
1741 |
+
"epoch": 2.936648904677324,
|
1742 |
+
"grad_norm": 1.416338562965393,
|
1743 |
+
"learning_rate": 5.2016171405103174e-08,
|
1744 |
+
"loss": 1.8404,
|
1745 |
+
"step": 1240
|
1746 |
+
},
|
1747 |
+
{
|
1748 |
+
"epoch": 2.9484902309058616,
|
1749 |
+
"grad_norm": 1.3145766258239746,
|
1750 |
+
"learning_rate": 3.393771922142741e-08,
|
1751 |
+
"loss": 2.0654,
|
1752 |
+
"step": 1245
|
1753 |
+
},
|
1754 |
+
{
|
1755 |
+
"epoch": 2.960331557134399,
|
1756 |
+
"grad_norm": 1.3440285921096802,
|
1757 |
+
"learning_rate": 1.9702677966507154e-08,
|
1758 |
+
"loss": 1.8111,
|
1759 |
+
"step": 1250
|
1760 |
+
},
|
1761 |
+
{
|
1762 |
+
"epoch": 2.9721728833629366,
|
1763 |
+
"grad_norm": 1.3247921466827393,
|
1764 |
+
"learning_rate": 9.31323905974113e-09,
|
1765 |
+
"loss": 1.8708,
|
1766 |
+
"step": 1255
|
1767 |
+
},
|
1768 |
+
{
|
1769 |
+
"epoch": 2.984014209591474,
|
1770 |
+
"grad_norm": 1.7957427501678467,
|
1771 |
+
"learning_rate": 2.771001907653226e-09,
|
1772 |
+
"loss": 1.8842,
|
1773 |
+
"step": 1260
|
1774 |
+
},
|
1775 |
+
{
|
1776 |
+
"epoch": 2.995855535820012,
|
1777 |
+
"grad_norm": 1.4069582223892212,
|
1778 |
+
"learning_rate": 7.697365768943864e-11,
|
1779 |
+
"loss": 1.9665,
|
1780 |
+
"step": 1265
|
1781 |
+
},
|
1782 |
+
{
|
1783 |
+
"epoch": 2.9982238010657194,
|
1784 |
+
"step": 1266,
|
1785 |
+
"total_flos": 6.019503790030848e+16,
|
1786 |
+
"train_loss": 1.9697479162170988,
|
1787 |
+
"train_runtime": 4932.4291,
|
1788 |
+
"train_samples_per_second": 4.109,
|
1789 |
+
"train_steps_per_second": 0.257
|
1790 |
}
|
1791 |
],
|
1792 |
"logging_steps": 5,
|
|
|
1794 |
"num_input_tokens_seen": 0,
|
1795 |
"num_train_epochs": 3,
|
1796 |
"save_steps": 100,
|
1797 |
+
"total_flos": 6.019503790030848e+16,
|
1798 |
"train_batch_size": 2,
|
1799 |
"trial_name": null,
|
1800 |
"trial_params": null
|