TooKeen commited on
Commit
ae29d7b
1 Parent(s): b7cb647

Upload folder using huggingface_hub

Browse files
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: togethercomputer/Mistral-7B-Instruct-v0.2
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 0.12.0
adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "togethercomputer/Mistral-7B-Instruct-v0.2",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 8,
14
+ "lora_dropout": 0.0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "down_proj",
24
+ "v_proj",
25
+ "q_proj",
26
+ "o_proj",
27
+ "up_proj",
28
+ "gate_proj",
29
+ "k_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:18015740b6d526d441c8d21c4a3c8c74793879e0e19a0a3d01557f55a2c164e4
3
+ size 83945296
special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": null,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "additional_special_tokens": [],
32
+ "bos_token": "<s>",
33
+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
34
+ "clean_up_tokenization_spaces": false,
35
+ "eos_token": "</s>",
36
+ "legacy": true,
37
+ "model_max_length": 32768,
38
+ "pad_token": "</s>",
39
+ "padding_side": "right",
40
+ "sp_model_kwargs": {},
41
+ "spaces_between_special_tokens": false,
42
+ "tokenizer_class": "LlamaTokenizer",
43
+ "unk_token": "<unk>",
44
+ "use_default_system_prompt": false
45
+ }
trainer_state.json ADDED
@@ -0,0 +1,565 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.0,
5
+ "eval_steps": 0,
6
+ "global_step": 76,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.013157894736842105,
13
+ "grad_norm": 3.5969951152801514,
14
+ "learning_rate": 9.868421052631579e-06,
15
+ "loss": 3.5568,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.02631578947368421,
20
+ "grad_norm": 4.185197830200195,
21
+ "learning_rate": 9.736842105263159e-06,
22
+ "loss": 4.0349,
23
+ "step": 2
24
+ },
25
+ {
26
+ "epoch": 0.039473684210526314,
27
+ "grad_norm": 3.4948582649230957,
28
+ "learning_rate": 9.605263157894737e-06,
29
+ "loss": 3.4982,
30
+ "step": 3
31
+ },
32
+ {
33
+ "epoch": 0.05263157894736842,
34
+ "grad_norm": 3.7073941230773926,
35
+ "learning_rate": 9.473684210526315e-06,
36
+ "loss": 3.6487,
37
+ "step": 4
38
+ },
39
+ {
40
+ "epoch": 0.06578947368421052,
41
+ "grad_norm": 4.189187049865723,
42
+ "learning_rate": 9.342105263157895e-06,
43
+ "loss": 3.9381,
44
+ "step": 5
45
+ },
46
+ {
47
+ "epoch": 0.07894736842105263,
48
+ "grad_norm": 4.8404541015625,
49
+ "learning_rate": 9.210526315789474e-06,
50
+ "loss": 4.1107,
51
+ "step": 6
52
+ },
53
+ {
54
+ "epoch": 0.09210526315789473,
55
+ "grad_norm": 3.8595361709594727,
56
+ "learning_rate": 9.078947368421054e-06,
57
+ "loss": 3.3677,
58
+ "step": 7
59
+ },
60
+ {
61
+ "epoch": 0.10526315789473684,
62
+ "grad_norm": 4.151785373687744,
63
+ "learning_rate": 8.947368421052632e-06,
64
+ "loss": 3.4079,
65
+ "step": 8
66
+ },
67
+ {
68
+ "epoch": 0.11842105263157894,
69
+ "grad_norm": 3.8082962036132812,
70
+ "learning_rate": 8.81578947368421e-06,
71
+ "loss": 3.3549,
72
+ "step": 9
73
+ },
74
+ {
75
+ "epoch": 0.13157894736842105,
76
+ "grad_norm": 3.9419312477111816,
77
+ "learning_rate": 8.68421052631579e-06,
78
+ "loss": 3.4935,
79
+ "step": 10
80
+ },
81
+ {
82
+ "epoch": 0.14473684210526316,
83
+ "grad_norm": 4.361544132232666,
84
+ "learning_rate": 8.552631578947368e-06,
85
+ "loss": 3.448,
86
+ "step": 11
87
+ },
88
+ {
89
+ "epoch": 0.15789473684210525,
90
+ "grad_norm": 3.8608157634735107,
91
+ "learning_rate": 8.421052631578948e-06,
92
+ "loss": 3.3588,
93
+ "step": 12
94
+ },
95
+ {
96
+ "epoch": 0.17105263157894737,
97
+ "grad_norm": 4.809046745300293,
98
+ "learning_rate": 8.289473684210526e-06,
99
+ "loss": 3.7738,
100
+ "step": 13
101
+ },
102
+ {
103
+ "epoch": 0.18421052631578946,
104
+ "grad_norm": 3.825930118560791,
105
+ "learning_rate": 8.157894736842106e-06,
106
+ "loss": 3.4686,
107
+ "step": 14
108
+ },
109
+ {
110
+ "epoch": 0.19736842105263158,
111
+ "grad_norm": 4.184592247009277,
112
+ "learning_rate": 8.026315789473685e-06,
113
+ "loss": 3.388,
114
+ "step": 15
115
+ },
116
+ {
117
+ "epoch": 0.21052631578947367,
118
+ "grad_norm": 4.1753668785095215,
119
+ "learning_rate": 7.894736842105265e-06,
120
+ "loss": 3.2729,
121
+ "step": 16
122
+ },
123
+ {
124
+ "epoch": 0.2236842105263158,
125
+ "grad_norm": 4.188427925109863,
126
+ "learning_rate": 7.763157894736843e-06,
127
+ "loss": 3.3862,
128
+ "step": 17
129
+ },
130
+ {
131
+ "epoch": 0.23684210526315788,
132
+ "grad_norm": 3.5322694778442383,
133
+ "learning_rate": 7.631578947368423e-06,
134
+ "loss": 3.1601,
135
+ "step": 18
136
+ },
137
+ {
138
+ "epoch": 0.25,
139
+ "grad_norm": 4.3005595207214355,
140
+ "learning_rate": 7.500000000000001e-06,
141
+ "loss": 3.2731,
142
+ "step": 19
143
+ },
144
+ {
145
+ "epoch": 0.2631578947368421,
146
+ "grad_norm": 4.415473461151123,
147
+ "learning_rate": 7.368421052631579e-06,
148
+ "loss": 3.1474,
149
+ "step": 20
150
+ },
151
+ {
152
+ "epoch": 0.27631578947368424,
153
+ "grad_norm": 4.977243900299072,
154
+ "learning_rate": 7.236842105263158e-06,
155
+ "loss": 3.227,
156
+ "step": 21
157
+ },
158
+ {
159
+ "epoch": 0.2894736842105263,
160
+ "grad_norm": 4.110137462615967,
161
+ "learning_rate": 7.1052631578947375e-06,
162
+ "loss": 2.8902,
163
+ "step": 22
164
+ },
165
+ {
166
+ "epoch": 0.3026315789473684,
167
+ "grad_norm": 4.749568939208984,
168
+ "learning_rate": 6.973684210526316e-06,
169
+ "loss": 3.2829,
170
+ "step": 23
171
+ },
172
+ {
173
+ "epoch": 0.3157894736842105,
174
+ "grad_norm": 4.500365257263184,
175
+ "learning_rate": 6.842105263157896e-06,
176
+ "loss": 2.9448,
177
+ "step": 24
178
+ },
179
+ {
180
+ "epoch": 0.32894736842105265,
181
+ "grad_norm": 4.0608744621276855,
182
+ "learning_rate": 6.710526315789474e-06,
183
+ "loss": 3.0899,
184
+ "step": 25
185
+ },
186
+ {
187
+ "epoch": 0.34210526315789475,
188
+ "grad_norm": 4.095396518707275,
189
+ "learning_rate": 6.578947368421054e-06,
190
+ "loss": 2.9888,
191
+ "step": 26
192
+ },
193
+ {
194
+ "epoch": 0.35526315789473684,
195
+ "grad_norm": 4.954774379730225,
196
+ "learning_rate": 6.447368421052632e-06,
197
+ "loss": 3.4578,
198
+ "step": 27
199
+ },
200
+ {
201
+ "epoch": 0.3684210526315789,
202
+ "grad_norm": 4.0194597244262695,
203
+ "learning_rate": 6.31578947368421e-06,
204
+ "loss": 2.807,
205
+ "step": 28
206
+ },
207
+ {
208
+ "epoch": 0.3815789473684211,
209
+ "grad_norm": 4.574712753295898,
210
+ "learning_rate": 6.18421052631579e-06,
211
+ "loss": 3.3466,
212
+ "step": 29
213
+ },
214
+ {
215
+ "epoch": 0.39473684210526316,
216
+ "grad_norm": 5.773961544036865,
217
+ "learning_rate": 6.0526315789473685e-06,
218
+ "loss": 3.519,
219
+ "step": 30
220
+ },
221
+ {
222
+ "epoch": 0.40789473684210525,
223
+ "grad_norm": 3.523261070251465,
224
+ "learning_rate": 5.921052631578948e-06,
225
+ "loss": 2.7265,
226
+ "step": 31
227
+ },
228
+ {
229
+ "epoch": 0.42105263157894735,
230
+ "grad_norm": 4.2967963218688965,
231
+ "learning_rate": 5.789473684210527e-06,
232
+ "loss": 2.9817,
233
+ "step": 32
234
+ },
235
+ {
236
+ "epoch": 0.4342105263157895,
237
+ "grad_norm": 4.2323689460754395,
238
+ "learning_rate": 5.657894736842106e-06,
239
+ "loss": 2.9753,
240
+ "step": 33
241
+ },
242
+ {
243
+ "epoch": 0.4473684210526316,
244
+ "grad_norm": 3.893044948577881,
245
+ "learning_rate": 5.526315789473685e-06,
246
+ "loss": 2.6951,
247
+ "step": 34
248
+ },
249
+ {
250
+ "epoch": 0.4605263157894737,
251
+ "grad_norm": 4.018922328948975,
252
+ "learning_rate": 5.394736842105264e-06,
253
+ "loss": 2.7226,
254
+ "step": 35
255
+ },
256
+ {
257
+ "epoch": 0.47368421052631576,
258
+ "grad_norm": 4.34171199798584,
259
+ "learning_rate": 5.263157894736842e-06,
260
+ "loss": 3.0148,
261
+ "step": 36
262
+ },
263
+ {
264
+ "epoch": 0.4868421052631579,
265
+ "grad_norm": 4.391392230987549,
266
+ "learning_rate": 5.131578947368422e-06,
267
+ "loss": 2.8676,
268
+ "step": 37
269
+ },
270
+ {
271
+ "epoch": 0.5,
272
+ "grad_norm": 4.058086395263672,
273
+ "learning_rate": 5e-06,
274
+ "loss": 2.9084,
275
+ "step": 38
276
+ },
277
+ {
278
+ "epoch": 0.5131578947368421,
279
+ "grad_norm": 4.01865816116333,
280
+ "learning_rate": 4.8684210526315795e-06,
281
+ "loss": 2.7218,
282
+ "step": 39
283
+ },
284
+ {
285
+ "epoch": 0.5263157894736842,
286
+ "grad_norm": 4.012227535247803,
287
+ "learning_rate": 4.736842105263158e-06,
288
+ "loss": 2.8061,
289
+ "step": 40
290
+ },
291
+ {
292
+ "epoch": 0.5394736842105263,
293
+ "grad_norm": 4.107736110687256,
294
+ "learning_rate": 4.605263157894737e-06,
295
+ "loss": 2.796,
296
+ "step": 41
297
+ },
298
+ {
299
+ "epoch": 0.5526315789473685,
300
+ "grad_norm": 4.0551862716674805,
301
+ "learning_rate": 4.473684210526316e-06,
302
+ "loss": 2.6791,
303
+ "step": 42
304
+ },
305
+ {
306
+ "epoch": 0.5657894736842105,
307
+ "grad_norm": 4.386580944061279,
308
+ "learning_rate": 4.342105263157895e-06,
309
+ "loss": 2.9243,
310
+ "step": 43
311
+ },
312
+ {
313
+ "epoch": 0.5789473684210527,
314
+ "grad_norm": 4.859345436096191,
315
+ "learning_rate": 4.210526315789474e-06,
316
+ "loss": 2.8425,
317
+ "step": 44
318
+ },
319
+ {
320
+ "epoch": 0.5921052631578947,
321
+ "grad_norm": 4.436668395996094,
322
+ "learning_rate": 4.078947368421053e-06,
323
+ "loss": 2.8771,
324
+ "step": 45
325
+ },
326
+ {
327
+ "epoch": 0.6052631578947368,
328
+ "grad_norm": 4.006519794464111,
329
+ "learning_rate": 3.947368421052632e-06,
330
+ "loss": 2.7562,
331
+ "step": 46
332
+ },
333
+ {
334
+ "epoch": 0.618421052631579,
335
+ "grad_norm": 3.805677652359009,
336
+ "learning_rate": 3.815789473684211e-06,
337
+ "loss": 2.6883,
338
+ "step": 47
339
+ },
340
+ {
341
+ "epoch": 0.631578947368421,
342
+ "grad_norm": 4.111331939697266,
343
+ "learning_rate": 3.6842105263157896e-06,
344
+ "loss": 2.686,
345
+ "step": 48
346
+ },
347
+ {
348
+ "epoch": 0.6447368421052632,
349
+ "grad_norm": 3.323714017868042,
350
+ "learning_rate": 3.5526315789473687e-06,
351
+ "loss": 2.3828,
352
+ "step": 49
353
+ },
354
+ {
355
+ "epoch": 0.6578947368421053,
356
+ "grad_norm": 4.244898319244385,
357
+ "learning_rate": 3.421052631578948e-06,
358
+ "loss": 2.865,
359
+ "step": 50
360
+ },
361
+ {
362
+ "epoch": 0.6710526315789473,
363
+ "grad_norm": 5.01881742477417,
364
+ "learning_rate": 3.289473684210527e-06,
365
+ "loss": 2.8533,
366
+ "step": 51
367
+ },
368
+ {
369
+ "epoch": 0.6842105263157895,
370
+ "grad_norm": 4.621983528137207,
371
+ "learning_rate": 3.157894736842105e-06,
372
+ "loss": 2.764,
373
+ "step": 52
374
+ },
375
+ {
376
+ "epoch": 0.6973684210526315,
377
+ "grad_norm": 4.3757710456848145,
378
+ "learning_rate": 3.0263157894736843e-06,
379
+ "loss": 2.6274,
380
+ "step": 53
381
+ },
382
+ {
383
+ "epoch": 0.7105263157894737,
384
+ "grad_norm": 4.757716655731201,
385
+ "learning_rate": 2.8947368421052634e-06,
386
+ "loss": 2.7931,
387
+ "step": 54
388
+ },
389
+ {
390
+ "epoch": 0.7236842105263158,
391
+ "grad_norm": 4.184610843658447,
392
+ "learning_rate": 2.7631578947368424e-06,
393
+ "loss": 2.7153,
394
+ "step": 55
395
+ },
396
+ {
397
+ "epoch": 0.7368421052631579,
398
+ "grad_norm": 3.97389554977417,
399
+ "learning_rate": 2.631578947368421e-06,
400
+ "loss": 2.6493,
401
+ "step": 56
402
+ },
403
+ {
404
+ "epoch": 0.75,
405
+ "grad_norm": 4.303612232208252,
406
+ "learning_rate": 2.5e-06,
407
+ "loss": 2.6206,
408
+ "step": 57
409
+ },
410
+ {
411
+ "epoch": 0.7631578947368421,
412
+ "grad_norm": 3.8477213382720947,
413
+ "learning_rate": 2.368421052631579e-06,
414
+ "loss": 2.4336,
415
+ "step": 58
416
+ },
417
+ {
418
+ "epoch": 0.7763157894736842,
419
+ "grad_norm": 4.191899299621582,
420
+ "learning_rate": 2.236842105263158e-06,
421
+ "loss": 2.6239,
422
+ "step": 59
423
+ },
424
+ {
425
+ "epoch": 0.7894736842105263,
426
+ "grad_norm": 3.8120546340942383,
427
+ "learning_rate": 2.105263157894737e-06,
428
+ "loss": 2.3935,
429
+ "step": 60
430
+ },
431
+ {
432
+ "epoch": 0.8026315789473685,
433
+ "grad_norm": 4.68777322769165,
434
+ "learning_rate": 1.973684210526316e-06,
435
+ "loss": 2.8501,
436
+ "step": 61
437
+ },
438
+ {
439
+ "epoch": 0.8157894736842105,
440
+ "grad_norm": 4.091485023498535,
441
+ "learning_rate": 1.8421052631578948e-06,
442
+ "loss": 2.4697,
443
+ "step": 62
444
+ },
445
+ {
446
+ "epoch": 0.8289473684210527,
447
+ "grad_norm": 4.707141399383545,
448
+ "learning_rate": 1.710526315789474e-06,
449
+ "loss": 2.7696,
450
+ "step": 63
451
+ },
452
+ {
453
+ "epoch": 0.8421052631578947,
454
+ "grad_norm": 4.358771324157715,
455
+ "learning_rate": 1.5789473684210526e-06,
456
+ "loss": 2.5899,
457
+ "step": 64
458
+ },
459
+ {
460
+ "epoch": 0.8552631578947368,
461
+ "grad_norm": 3.9348034858703613,
462
+ "learning_rate": 1.4473684210526317e-06,
463
+ "loss": 2.568,
464
+ "step": 65
465
+ },
466
+ {
467
+ "epoch": 0.868421052631579,
468
+ "grad_norm": 4.441805362701416,
469
+ "learning_rate": 1.3157894736842106e-06,
470
+ "loss": 2.5547,
471
+ "step": 66
472
+ },
473
+ {
474
+ "epoch": 0.881578947368421,
475
+ "grad_norm": 4.700938701629639,
476
+ "learning_rate": 1.1842105263157894e-06,
477
+ "loss": 2.7651,
478
+ "step": 67
479
+ },
480
+ {
481
+ "epoch": 0.8947368421052632,
482
+ "grad_norm": 3.856534957885742,
483
+ "learning_rate": 1.0526315789473685e-06,
484
+ "loss": 2.4805,
485
+ "step": 68
486
+ },
487
+ {
488
+ "epoch": 0.9078947368421053,
489
+ "grad_norm": 4.3660149574279785,
490
+ "learning_rate": 9.210526315789474e-07,
491
+ "loss": 2.5027,
492
+ "step": 69
493
+ },
494
+ {
495
+ "epoch": 0.9210526315789473,
496
+ "grad_norm": 4.625879287719727,
497
+ "learning_rate": 7.894736842105263e-07,
498
+ "loss": 3.0098,
499
+ "step": 70
500
+ },
501
+ {
502
+ "epoch": 0.9342105263157895,
503
+ "grad_norm": 3.837646007537842,
504
+ "learning_rate": 6.578947368421053e-07,
505
+ "loss": 2.4544,
506
+ "step": 71
507
+ },
508
+ {
509
+ "epoch": 0.9473684210526315,
510
+ "grad_norm": 3.6256585121154785,
511
+ "learning_rate": 5.263157894736843e-07,
512
+ "loss": 2.2905,
513
+ "step": 72
514
+ },
515
+ {
516
+ "epoch": 0.9605263157894737,
517
+ "grad_norm": 4.403687000274658,
518
+ "learning_rate": 3.9473684210526315e-07,
519
+ "loss": 2.7397,
520
+ "step": 73
521
+ },
522
+ {
523
+ "epoch": 0.9736842105263158,
524
+ "grad_norm": 3.8329477310180664,
525
+ "learning_rate": 2.6315789473684213e-07,
526
+ "loss": 2.4028,
527
+ "step": 74
528
+ },
529
+ {
530
+ "epoch": 0.9868421052631579,
531
+ "grad_norm": 3.729228973388672,
532
+ "learning_rate": 1.3157894736842107e-07,
533
+ "loss": 2.4891,
534
+ "step": 75
535
+ },
536
+ {
537
+ "epoch": 1.0,
538
+ "grad_norm": 3.699434995651245,
539
+ "learning_rate": 0.0,
540
+ "loss": 2.4679,
541
+ "step": 76
542
+ }
543
+ ],
544
+ "logging_steps": 1.0,
545
+ "max_steps": 76,
546
+ "num_input_tokens_seen": 0,
547
+ "num_train_epochs": 1,
548
+ "save_steps": 0,
549
+ "stateful_callbacks": {
550
+ "TrainerControl": {
551
+ "args": {
552
+ "should_epoch_stop": false,
553
+ "should_evaluate": false,
554
+ "should_log": false,
555
+ "should_save": true,
556
+ "should_training_stop": true
557
+ },
558
+ "attributes": {}
559
+ }
560
+ },
561
+ "total_flos": 1.0656232298564813e+17,
562
+ "train_batch_size": 1,
563
+ "trial_name": null,
564
+ "trial_params": null
565
+ }