PEFT
Safetensors
Gege24 commited on
Commit
7af42e0
·
verified ·
1 Parent(s): 1af7d3e

Upload task output fa30d435-3229-4c56-871d-51ad38cfbe7a

Browse files
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: None
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
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
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
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 0.15.1
adapter_config.json ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": null,
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 512,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.1,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "r": 128,
24
+ "rank_pattern": {},
25
+ "revision": null,
26
+ "target_modules": [
27
+ "up_proj",
28
+ "k_proj",
29
+ "down_proj",
30
+ "gate_proj",
31
+ "q_proj",
32
+ "v_proj",
33
+ "o_proj"
34
+ ],
35
+ "task_type": "CAUSAL_LM",
36
+ "trainable_token_indices": null,
37
+ "use_dora": false,
38
+ "use_rslora": false
39
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6637822566c77111fc42fe30acbd605342b8492cf43c1dd9537249cd5bfd4508
3
+ size 578859568
loss.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ swa,3_checkpoints_averaged
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fd13b1f10a586a5482f9616069647bd73d5b14eb85af5e6515dad980e4df2e6d
3
+ size 289452768
special_tokens_map.json ADDED
@@ -0,0 +1,49 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|endoftext|>",
4
+ "<|im_start|>",
5
+ "<|im_end|>",
6
+ "<repo_name>",
7
+ "<reponame>",
8
+ "<file_sep>",
9
+ "<filename>",
10
+ "<gh_stars>",
11
+ "<issue_start>",
12
+ "<issue_comment>",
13
+ "<issue_closed>",
14
+ "<jupyter_start>",
15
+ "<jupyter_text>",
16
+ "<jupyter_code>",
17
+ "<jupyter_output>",
18
+ "<jupyter_script>",
19
+ "<empty_output>"
20
+ ],
21
+ "bos_token": {
22
+ "content": "<|endoftext|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false
27
+ },
28
+ "eos_token": {
29
+ "content": "<|endoftext|>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false
34
+ },
35
+ "pad_token": {
36
+ "content": "<empty_output>",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false
41
+ },
42
+ "unk_token": {
43
+ "content": "<|endoftext|>",
44
+ "lstrip": false,
45
+ "normalized": false,
46
+ "rstrip": false,
47
+ "single_word": false
48
+ }
49
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,170 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "added_tokens_decoder": {
4
+ "0": {
5
+ "content": "<|endoftext|>",
6
+ "lstrip": false,
7
+ "normalized": false,
8
+ "rstrip": false,
9
+ "single_word": false,
10
+ "special": true
11
+ },
12
+ "1": {
13
+ "content": "<|im_start|>",
14
+ "lstrip": false,
15
+ "normalized": false,
16
+ "rstrip": false,
17
+ "single_word": false,
18
+ "special": true
19
+ },
20
+ "2": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false,
26
+ "special": true
27
+ },
28
+ "3": {
29
+ "content": "<repo_name>",
30
+ "lstrip": false,
31
+ "normalized": false,
32
+ "rstrip": false,
33
+ "single_word": false,
34
+ "special": true
35
+ },
36
+ "4": {
37
+ "content": "<reponame>",
38
+ "lstrip": false,
39
+ "normalized": false,
40
+ "rstrip": false,
41
+ "single_word": false,
42
+ "special": true
43
+ },
44
+ "5": {
45
+ "content": "<file_sep>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false,
50
+ "special": true
51
+ },
52
+ "6": {
53
+ "content": "<filename>",
54
+ "lstrip": false,
55
+ "normalized": false,
56
+ "rstrip": false,
57
+ "single_word": false,
58
+ "special": true
59
+ },
60
+ "7": {
61
+ "content": "<gh_stars>",
62
+ "lstrip": false,
63
+ "normalized": false,
64
+ "rstrip": false,
65
+ "single_word": false,
66
+ "special": true
67
+ },
68
+ "8": {
69
+ "content": "<issue_start>",
70
+ "lstrip": false,
71
+ "normalized": false,
72
+ "rstrip": false,
73
+ "single_word": false,
74
+ "special": true
75
+ },
76
+ "9": {
77
+ "content": "<issue_comment>",
78
+ "lstrip": false,
79
+ "normalized": false,
80
+ "rstrip": false,
81
+ "single_word": false,
82
+ "special": true
83
+ },
84
+ "10": {
85
+ "content": "<issue_closed>",
86
+ "lstrip": false,
87
+ "normalized": false,
88
+ "rstrip": false,
89
+ "single_word": false,
90
+ "special": true
91
+ },
92
+ "11": {
93
+ "content": "<jupyter_start>",
94
+ "lstrip": false,
95
+ "normalized": false,
96
+ "rstrip": false,
97
+ "single_word": false,
98
+ "special": true
99
+ },
100
+ "12": {
101
+ "content": "<jupyter_text>",
102
+ "lstrip": false,
103
+ "normalized": false,
104
+ "rstrip": false,
105
+ "single_word": false,
106
+ "special": true
107
+ },
108
+ "13": {
109
+ "content": "<jupyter_code>",
110
+ "lstrip": false,
111
+ "normalized": false,
112
+ "rstrip": false,
113
+ "single_word": false,
114
+ "special": true
115
+ },
116
+ "14": {
117
+ "content": "<jupyter_output>",
118
+ "lstrip": false,
119
+ "normalized": false,
120
+ "rstrip": false,
121
+ "single_word": false,
122
+ "special": true
123
+ },
124
+ "15": {
125
+ "content": "<jupyter_script>",
126
+ "lstrip": false,
127
+ "normalized": false,
128
+ "rstrip": false,
129
+ "single_word": false,
130
+ "special": true
131
+ },
132
+ "16": {
133
+ "content": "<empty_output>",
134
+ "lstrip": false,
135
+ "normalized": false,
136
+ "rstrip": false,
137
+ "single_word": false,
138
+ "special": true
139
+ }
140
+ },
141
+ "additional_special_tokens": [
142
+ "<|endoftext|>",
143
+ "<|im_start|>",
144
+ "<|im_end|>",
145
+ "<repo_name>",
146
+ "<reponame>",
147
+ "<file_sep>",
148
+ "<filename>",
149
+ "<gh_stars>",
150
+ "<issue_start>",
151
+ "<issue_comment>",
152
+ "<issue_closed>",
153
+ "<jupyter_start>",
154
+ "<jupyter_text>",
155
+ "<jupyter_code>",
156
+ "<jupyter_output>",
157
+ "<jupyter_script>",
158
+ "<empty_output>"
159
+ ],
160
+ "bos_token": "<|endoftext|>",
161
+ "clean_up_tokenization_spaces": false,
162
+ "eos_token": "<|endoftext|>",
163
+ "extra_special_tokens": {},
164
+ "model_max_length": 1000000000000000019884624838656,
165
+ "pad_token": "<empty_output>",
166
+ "padding_side": "left",
167
+ "tokenizer_class": "GPT2Tokenizer",
168
+ "unk_token": "<|endoftext|>",
169
+ "vocab_size": 49152
170
+ }
trainer_state.json ADDED
@@ -0,0 +1,646 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 3.0,
6
+ "eval_steps": 500,
7
+ "global_step": 420,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.03571428571428571,
14
+ "grad_norm": 0.44878774881362915,
15
+ "learning_rate": 0.000289521783910996,
16
+ "loss": 3.3605,
17
+ "step": 5
18
+ },
19
+ {
20
+ "epoch": 0.07142857142857142,
21
+ "grad_norm": 0.325467973947525,
22
+ "learning_rate": 0.0003618400166398465,
23
+ "loss": 2.8945,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.10714285714285714,
28
+ "grad_norm": 0.2423306256532669,
29
+ "learning_rate": 0.0003615873730705915,
30
+ "loss": 2.6612,
31
+ "step": 15
32
+ },
33
+ {
34
+ "epoch": 0.14285714285714285,
35
+ "grad_norm": 0.2094593495130539,
36
+ "learning_rate": 0.000361140772483858,
37
+ "loss": 2.5949,
38
+ "step": 20
39
+ },
40
+ {
41
+ "epoch": 0.17857142857142858,
42
+ "grad_norm": 0.2044210284948349,
43
+ "learning_rate": 0.00036050085463068467,
44
+ "loss": 2.5521,
45
+ "step": 25
46
+ },
47
+ {
48
+ "epoch": 0.21428571428571427,
49
+ "grad_norm": 0.23538050055503845,
50
+ "learning_rate": 0.0003596685361872319,
51
+ "loss": 2.492,
52
+ "step": 30
53
+ },
54
+ {
55
+ "epoch": 0.25,
56
+ "grad_norm": 0.1984870284795761,
57
+ "learning_rate": 0.0003586450094416527,
58
+ "loss": 2.5206,
59
+ "step": 35
60
+ },
61
+ {
62
+ "epoch": 0.2857142857142857,
63
+ "grad_norm": 0.14157792925834656,
64
+ "learning_rate": 0.0003574317405861506,
65
+ "loss": 2.4296,
66
+ "step": 40
67
+ },
68
+ {
69
+ "epoch": 0.32142857142857145,
70
+ "grad_norm": 0.12453815340995789,
71
+ "learning_rate": 0.00035603046761667424,
72
+ "loss": 2.44,
73
+ "step": 45
74
+ },
75
+ {
76
+ "epoch": 0.35714285714285715,
77
+ "grad_norm": 0.11900381743907928,
78
+ "learning_rate": 0.0003544431978432544,
79
+ "loss": 2.4788,
80
+ "step": 50
81
+ },
82
+ {
83
+ "epoch": 0.39285714285714285,
84
+ "grad_norm": 0.19382521510124207,
85
+ "learning_rate": 0.00035267220501455183,
86
+ "loss": 2.4395,
87
+ "step": 55
88
+ },
89
+ {
90
+ "epoch": 0.42857142857142855,
91
+ "grad_norm": 0.184844508767128,
92
+ "learning_rate": 0.00035072002606073425,
93
+ "loss": 2.3968,
94
+ "step": 60
95
+ },
96
+ {
97
+ "epoch": 0.4642857142857143,
98
+ "grad_norm": 0.15302661061286926,
99
+ "learning_rate": 0.0003485894574593484,
100
+ "loss": 2.386,
101
+ "step": 65
102
+ },
103
+ {
104
+ "epoch": 0.5,
105
+ "grad_norm": 0.14385174214839935,
106
+ "learning_rate": 0.00034628355122939266,
107
+ "loss": 2.3891,
108
+ "step": 70
109
+ },
110
+ {
111
+ "epoch": 0.5357142857142857,
112
+ "grad_norm": 0.1122179701924324,
113
+ "learning_rate": 0.0003438056105593294,
114
+ "loss": 2.4124,
115
+ "step": 75
116
+ },
117
+ {
118
+ "epoch": 0.5714285714285714,
119
+ "grad_norm": 0.12257640808820724,
120
+ "learning_rate": 0.0003411591850752994,
121
+ "loss": 2.379,
122
+ "step": 80
123
+ },
124
+ {
125
+ "epoch": 0.6071428571428571,
126
+ "grad_norm": 0.11705131083726883,
127
+ "learning_rate": 0.0003383480657563163,
128
+ "loss": 2.3352,
129
+ "step": 85
130
+ },
131
+ {
132
+ "epoch": 0.6428571428571429,
133
+ "grad_norm": 0.11879861354827881,
134
+ "learning_rate": 0.0003353762795037261,
135
+ "loss": 2.3836,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 0.6785714285714286,
140
+ "grad_norm": 0.12045249342918396,
141
+ "learning_rate": 0.0003322480833727093,
142
+ "loss": 2.3884,
143
+ "step": 95
144
+ },
145
+ {
146
+ "epoch": 0.7142857142857143,
147
+ "grad_norm": 0.12423133105039597,
148
+ "learning_rate": 0.00032896795847409084,
149
+ "loss": 2.346,
150
+ "step": 100
151
+ },
152
+ {
153
+ "epoch": 0.75,
154
+ "grad_norm": 0.14303036034107208,
155
+ "learning_rate": 0.00032554060355519153,
156
+ "loss": 2.3621,
157
+ "step": 105
158
+ },
159
+ {
160
+ "epoch": 0.7857142857142857,
161
+ "grad_norm": 0.1502680629491806,
162
+ "learning_rate": 0.00032197092826891826,
163
+ "loss": 2.2704,
164
+ "step": 110
165
+ },
166
+ {
167
+ "epoch": 0.8214285714285714,
168
+ "grad_norm": 0.13060663640499115,
169
+ "learning_rate": 0.00031826404614073307,
170
+ "loss": 2.3163,
171
+ "step": 115
172
+ },
173
+ {
174
+ "epoch": 0.8571428571428571,
175
+ "grad_norm": 0.13510695099830627,
176
+ "learning_rate": 0.00031442526724357743,
177
+ "loss": 2.321,
178
+ "step": 120
179
+ },
180
+ {
181
+ "epoch": 0.8928571428571429,
182
+ "grad_norm": 0.12903311848640442,
183
+ "learning_rate": 0.0003104600905912439,
184
+ "loss": 2.2986,
185
+ "step": 125
186
+ },
187
+ {
188
+ "epoch": 0.9285714285714286,
189
+ "grad_norm": 0.12716606259346008,
190
+ "learning_rate": 0.0003063741962610917,
191
+ "loss": 2.2794,
192
+ "step": 130
193
+ },
194
+ {
195
+ "epoch": 0.9642857142857143,
196
+ "grad_norm": 0.14283885061740875,
197
+ "learning_rate": 0.0003021734372573907,
198
+ "loss": 2.2997,
199
+ "step": 135
200
+ },
201
+ {
202
+ "epoch": 1.0,
203
+ "grad_norm": 0.1486726701259613,
204
+ "learning_rate": 0.00029786383112694937,
205
+ "loss": 2.3651,
206
+ "step": 140
207
+ },
208
+ {
209
+ "epoch": 1.0,
210
+ "eval_loss": 2.305704355239868,
211
+ "eval_runtime": 4.346,
212
+ "eval_samples_per_second": 12.885,
213
+ "eval_steps_per_second": 12.885,
214
+ "step": 140
215
+ },
216
+ {
217
+ "epoch": 1.0357142857142858,
218
+ "grad_norm": 0.1466517597436905,
219
+ "learning_rate": 0.0002934515513390363,
220
+ "loss": 2.2312,
221
+ "step": 145
222
+ },
223
+ {
224
+ "epoch": 1.0714285714285714,
225
+ "grad_norm": 0.13890157639980316,
226
+ "learning_rate": 0.0002889429184419459,
227
+ "loss": 2.1697,
228
+ "step": 150
229
+ },
230
+ {
231
+ "epoch": 1.1071428571428572,
232
+ "grad_norm": 0.12447746843099594,
233
+ "learning_rate": 0.0002843443910088731,
234
+ "loss": 2.1876,
235
+ "step": 155
236
+ },
237
+ {
238
+ "epoch": 1.1428571428571428,
239
+ "grad_norm": 0.14858925342559814,
240
+ "learning_rate": 0.0002796625563860696,
241
+ "loss": 2.2529,
242
+ "step": 160
243
+ },
244
+ {
245
+ "epoch": 1.1785714285714286,
246
+ "grad_norm": 0.14622247219085693,
247
+ "learning_rate": 0.00027490412125653413,
248
+ "loss": 2.1692,
249
+ "step": 165
250
+ },
251
+ {
252
+ "epoch": 1.2142857142857142,
253
+ "grad_norm": 0.16352051496505737,
254
+ "learning_rate": 0.0002700759020327533,
255
+ "loss": 2.1683,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 1.25,
260
+ "grad_norm": 0.15044339001178741,
261
+ "learning_rate": 0.0002651848150922565,
262
+ "loss": 2.208,
263
+ "step": 175
264
+ },
265
+ {
266
+ "epoch": 1.2857142857142856,
267
+ "grad_norm": 0.18973936140537262,
268
+ "learning_rate": 0.00026023786686997193,
269
+ "loss": 2.1757,
270
+ "step": 180
271
+ },
272
+ {
273
+ "epoch": 1.3214285714285714,
274
+ "grad_norm": 0.1430087834596634,
275
+ "learning_rate": 0.00025524214382157567,
276
+ "loss": 2.1456,
277
+ "step": 185
278
+ },
279
+ {
280
+ "epoch": 1.3571428571428572,
281
+ "grad_norm": 0.15100987255573273,
282
+ "learning_rate": 0.00025020480227221244,
283
+ "loss": 2.1492,
284
+ "step": 190
285
+ },
286
+ {
287
+ "epoch": 1.3928571428571428,
288
+ "grad_norm": 0.1682235598564148,
289
+ "learning_rate": 0.00024513305816512866,
290
+ "loss": 2.1298,
291
+ "step": 195
292
+ },
293
+ {
294
+ "epoch": 1.4285714285714286,
295
+ "grad_norm": 0.13889002799987793,
296
+ "learning_rate": 0.0002400341767249034,
297
+ "loss": 2.1426,
298
+ "step": 200
299
+ },
300
+ {
301
+ "epoch": 1.4642857142857144,
302
+ "grad_norm": 0.15031439065933228,
303
+ "learning_rate": 0.00023491546205008394,
304
+ "loss": 2.1629,
305
+ "step": 205
306
+ },
307
+ {
308
+ "epoch": 1.5,
309
+ "grad_norm": 0.15855388343334198,
310
+ "learning_rate": 0.000229784246650135,
311
+ "loss": 2.1245,
312
+ "step": 210
313
+ },
314
+ {
315
+ "epoch": 1.5357142857142856,
316
+ "grad_norm": 0.1361117959022522,
317
+ "learning_rate": 0.0002246478809416899,
318
+ "loss": 2.1539,
319
+ "step": 215
320
+ },
321
+ {
322
+ "epoch": 1.5714285714285714,
323
+ "grad_norm": 0.1389189511537552,
324
+ "learning_rate": 0.000219513722719149,
325
+ "loss": 2.1689,
326
+ "step": 220
327
+ },
328
+ {
329
+ "epoch": 1.6071428571428572,
330
+ "grad_norm": 0.14022548496723175,
331
+ "learning_rate": 0.00021438912661471057,
332
+ "loss": 2.1066,
333
+ "step": 225
334
+ },
335
+ {
336
+ "epoch": 1.6428571428571428,
337
+ "grad_norm": 0.15505997836589813,
338
+ "learning_rate": 0.00020928143356293064,
339
+ "loss": 2.1704,
340
+ "step": 230
341
+ },
342
+ {
343
+ "epoch": 1.6785714285714286,
344
+ "grad_norm": 0.15153466165065765,
345
+ "learning_rate": 0.00020419796028490518,
346
+ "loss": 2.1221,
347
+ "step": 235
348
+ },
349
+ {
350
+ "epoch": 1.7142857142857144,
351
+ "grad_norm": 0.15661795437335968,
352
+ "learning_rate": 0.00019914598880713764,
353
+ "loss": 2.1085,
354
+ "step": 240
355
+ },
356
+ {
357
+ "epoch": 1.75,
358
+ "grad_norm": 0.18082356452941895,
359
+ "learning_rate": 0.00019413275603010594,
360
+ "loss": 2.1192,
361
+ "step": 245
362
+ },
363
+ {
364
+ "epoch": 1.7857142857142856,
365
+ "grad_norm": 0.1475025713443756,
366
+ "learning_rate": 0.00018916544336147238,
367
+ "loss": 2.1576,
368
+ "step": 250
369
+ },
370
+ {
371
+ "epoch": 1.8214285714285714,
372
+ "grad_norm": 0.1800713986158371,
373
+ "learning_rate": 0.00018425116642878646,
374
+ "loss": 2.2125,
375
+ "step": 255
376
+ },
377
+ {
378
+ "epoch": 1.8571428571428572,
379
+ "grad_norm": 0.1504836529493332,
380
+ "learning_rate": 0.0001793969648864165,
381
+ "loss": 2.1063,
382
+ "step": 260
383
+ },
384
+ {
385
+ "epoch": 1.8928571428571428,
386
+ "grad_norm": 0.15903660655021667,
387
+ "learning_rate": 0.0001746097923313131,
388
+ "loss": 2.1268,
389
+ "step": 265
390
+ },
391
+ {
392
+ "epoch": 1.9285714285714286,
393
+ "grad_norm": 0.17211540043354034,
394
+ "learning_rate": 0.00016989650634204837,
395
+ "loss": 2.1333,
396
+ "step": 270
397
+ },
398
+ {
399
+ "epoch": 1.9642857142857144,
400
+ "grad_norm": 0.15337097644805908,
401
+ "learning_rate": 0.0001652638586554003,
402
+ "loss": 2.1328,
403
+ "step": 275
404
+ },
405
+ {
406
+ "epoch": 2.0,
407
+ "grad_norm": 0.15568628907203674,
408
+ "learning_rate": 0.00016071848549455535,
409
+ "loss": 2.151,
410
+ "step": 280
411
+ },
412
+ {
413
+ "epoch": 2.0,
414
+ "eval_loss": 2.22261381149292,
415
+ "eval_runtime": 4.2486,
416
+ "eval_samples_per_second": 13.181,
417
+ "eval_steps_per_second": 13.181,
418
+ "step": 280
419
+ },
420
+ {
421
+ "epoch": 2.0357142857142856,
422
+ "grad_norm": 0.16075798869132996,
423
+ "learning_rate": 0.00015626689806278225,
424
+ "loss": 2.0259,
425
+ "step": 285
426
+ },
427
+ {
428
+ "epoch": 2.0714285714285716,
429
+ "grad_norm": 0.17610718309879303,
430
+ "learning_rate": 0.00015191547321619653,
431
+ "loss": 2.0075,
432
+ "step": 290
433
+ },
434
+ {
435
+ "epoch": 2.107142857142857,
436
+ "grad_norm": 0.16602124273777008,
437
+ "learning_rate": 0.00014767044432897506,
438
+ "loss": 2.038,
439
+ "step": 295
440
+ },
441
+ {
442
+ "epoch": 2.142857142857143,
443
+ "grad_norm": 0.16692619025707245,
444
+ "learning_rate": 0.0001435378923641078,
445
+ "loss": 1.9613,
446
+ "step": 300
447
+ },
448
+ {
449
+ "epoch": 2.1785714285714284,
450
+ "grad_norm": 0.18126952648162842,
451
+ "learning_rate": 0.000139523737162477,
452
+ "loss": 1.9858,
453
+ "step": 305
454
+ },
455
+ {
456
+ "epoch": 2.2142857142857144,
457
+ "grad_norm": 0.17799189686775208,
458
+ "learning_rate": 0.00013563372896274205,
459
+ "loss": 1.9845,
460
+ "step": 310
461
+ },
462
+ {
463
+ "epoch": 2.25,
464
+ "grad_norm": 0.16581512987613678,
465
+ "learning_rate": 0.00013187344016417777,
466
+ "loss": 1.9754,
467
+ "step": 315
468
+ },
469
+ {
470
+ "epoch": 2.2857142857142856,
471
+ "grad_norm": 0.18213392794132233,
472
+ "learning_rate": 0.00012824825734426663,
473
+ "loss": 2.0338,
474
+ "step": 320
475
+ },
476
+ {
477
+ "epoch": 2.3214285714285716,
478
+ "grad_norm": 0.20415815711021423,
479
+ "learning_rate": 0.00012476337354247802,
480
+ "loss": 1.9789,
481
+ "step": 325
482
+ },
483
+ {
484
+ "epoch": 2.357142857142857,
485
+ "grad_norm": 0.18837185204029083,
486
+ "learning_rate": 0.00012142378082128922,
487
+ "loss": 1.9793,
488
+ "step": 330
489
+ },
490
+ {
491
+ "epoch": 2.392857142857143,
492
+ "grad_norm": 0.18530172109603882,
493
+ "learning_rate": 0.00011823426311510409,
494
+ "loss": 1.9982,
495
+ "step": 335
496
+ },
497
+ {
498
+ "epoch": 2.4285714285714284,
499
+ "grad_norm": 0.18085235357284546,
500
+ "learning_rate": 0.00011519938937731338,
501
+ "loss": 1.9721,
502
+ "step": 340
503
+ },
504
+ {
505
+ "epoch": 2.4642857142857144,
506
+ "grad_norm": 0.17293037474155426,
507
+ "learning_rate": 0.00011232350703531239,
508
+ "loss": 1.962,
509
+ "step": 345
510
+ },
511
+ {
512
+ "epoch": 2.5,
513
+ "grad_norm": 0.17826664447784424,
514
+ "learning_rate": 0.00010961073576285371,
515
+ "loss": 1.9523,
516
+ "step": 350
517
+ },
518
+ {
519
+ "epoch": 2.5357142857142856,
520
+ "grad_norm": 0.17852868139743805,
521
+ "learning_rate": 0.00010706496157865393,
522
+ "loss": 1.9601,
523
+ "step": 355
524
+ },
525
+ {
526
+ "epoch": 2.571428571428571,
527
+ "grad_norm": 0.1897851526737213,
528
+ "learning_rate": 0.00010468983127970931,
529
+ "loss": 1.9985,
530
+ "step": 360
531
+ },
532
+ {
533
+ "epoch": 2.607142857142857,
534
+ "grad_norm": 0.17821991443634033,
535
+ "learning_rate": 0.00010248874721729424,
536
+ "loss": 1.9627,
537
+ "step": 365
538
+ },
539
+ {
540
+ "epoch": 2.642857142857143,
541
+ "grad_norm": 0.16785487532615662,
542
+ "learning_rate": 0.00010046486242312592,
543
+ "loss": 1.9742,
544
+ "step": 370
545
+ },
546
+ {
547
+ "epoch": 2.678571428571429,
548
+ "grad_norm": 0.19044014811515808,
549
+ "learning_rate": 9.862107609267647e-05,
550
+ "loss": 1.9747,
551
+ "step": 375
552
+ },
553
+ {
554
+ "epoch": 2.7142857142857144,
555
+ "grad_norm": 0.18507127463817596,
556
+ "learning_rate": 9.696002943210377e-05,
557
+ "loss": 1.9357,
558
+ "step": 380
559
+ },
560
+ {
561
+ "epoch": 2.75,
562
+ "grad_norm": 0.17904826998710632,
563
+ "learning_rate": 9.548410187474875e-05,
564
+ "loss": 1.994,
565
+ "step": 385
566
+ },
567
+ {
568
+ "epoch": 2.7857142857142856,
569
+ "grad_norm": 0.19766312837600708,
570
+ "learning_rate": 9.419540767262022e-05,
571
+ "loss": 1.9463,
572
+ "step": 390
573
+ },
574
+ {
575
+ "epoch": 2.821428571428571,
576
+ "grad_norm": 0.1815754771232605,
577
+ "learning_rate": 9.309579286774919e-05,
578
+ "loss": 1.9613,
579
+ "step": 395
580
+ },
581
+ {
582
+ "epoch": 2.857142857142857,
583
+ "grad_norm": 0.19703654944896698,
584
+ "learning_rate": 9.21868326477514e-05,
585
+ "loss": 2.0123,
586
+ "step": 400
587
+ },
588
+ {
589
+ "epoch": 2.892857142857143,
590
+ "grad_norm": 0.18807531893253326,
591
+ "learning_rate": 9.146982908938626e-05,
592
+ "loss": 1.9648,
593
+ "step": 405
594
+ },
595
+ {
596
+ "epoch": 2.928571428571429,
597
+ "grad_norm": 0.2164294570684433,
598
+ "learning_rate": 9.094580929334454e-05,
599
+ "loss": 1.997,
600
+ "step": 410
601
+ },
602
+ {
603
+ "epoch": 2.9642857142857144,
604
+ "grad_norm": 0.1642838567495346,
605
+ "learning_rate": 9.061552391293631e-05,
606
+ "loss": 1.9741,
607
+ "step": 415
608
+ },
609
+ {
610
+ "epoch": 3.0,
611
+ "grad_norm": 0.19275926053524017,
612
+ "learning_rate": 9.047944607878754e-05,
613
+ "loss": 1.9786,
614
+ "step": 420
615
+ },
616
+ {
617
+ "epoch": 3.0,
618
+ "eval_loss": 2.21170711517334,
619
+ "eval_runtime": 4.2499,
620
+ "eval_samples_per_second": 13.177,
621
+ "eval_steps_per_second": 13.177,
622
+ "step": 420
623
+ }
624
+ ],
625
+ "logging_steps": 5,
626
+ "max_steps": 420,
627
+ "num_input_tokens_seen": 0,
628
+ "num_train_epochs": 3,
629
+ "save_steps": 140,
630
+ "stateful_callbacks": {
631
+ "TrainerControl": {
632
+ "args": {
633
+ "should_epoch_stop": false,
634
+ "should_evaluate": false,
635
+ "should_log": false,
636
+ "should_save": true,
637
+ "should_training_stop": true
638
+ },
639
+ "attributes": {}
640
+ }
641
+ },
642
+ "total_flos": 2.26490868301824e+17,
643
+ "train_batch_size": 25,
644
+ "trial_name": null,
645
+ "trial_params": null
646
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d2edb30c60d48614f93c80c6cc7086cb52ee4874bd8dd170c29a97ebabd1d1c3
3
+ size 5624
vocab.json ADDED
The diff for this file is too large to render. See raw diff