RajGana commited on
Commit
ea38030
·
verified ·
1 Parent(s): c4e4c7e

Upload folder using huggingface_hub

Browse files
README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: codellama/CodeLlama-7b-Instruct-hf
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:codellama/CodeLlama-7b-Instruct-hf
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- 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. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ 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).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.19.1
adapter_config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "codellama/CodeLlama-7b-Instruct-hf",
7
+ "bias": "none",
8
+ "corda_config": null,
9
+ "ensure_weight_tying": false,
10
+ "eva_config": null,
11
+ "exclude_modules": null,
12
+ "fan_in_fan_out": false,
13
+ "inference_mode": true,
14
+ "init_lora_weights": true,
15
+ "layer_replication": null,
16
+ "layers_pattern": null,
17
+ "layers_to_transform": null,
18
+ "loftq_config": {},
19
+ "lora_alpha": 128,
20
+ "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 64,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "v_proj",
34
+ "q_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_bdlora": null,
40
+ "use_dora": false,
41
+ "use_qalora": false,
42
+ "use_rslora": false
43
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aaaac375245c10bee51426f19ee662e6d385feacaf8ebdd6ad4b56b6d474816e
3
+ size 67126232
chat_template.jinja ADDED
@@ -0,0 +1 @@
 
 
1
+ {% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content | trim + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content | trim + ' ' + eos_token }}{% endif %}{% endfor %}
optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca91f528f599b98de119af1165c5f56a583c8595908ed58b07b62c0a90643acb
3
+ size 134326347
rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d53414066a8cc66c5f164b0d52592a475451894f47d53a0ffe41f86139ca54cc
3
+ size 14645
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:35cf3627ef9f8df15d9c4864a49048fcd16b96fc23317a4c7fa79a020eac80c9
3
+ size 1465
special_tokens_map.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "▁<PRE>",
4
+ "▁<MID>",
5
+ "▁<SUF>",
6
+ "▁<EOT>"
7
+ ],
8
+ "bos_token": {
9
+ "content": "<s>",
10
+ "lstrip": false,
11
+ "normalized": false,
12
+ "rstrip": false,
13
+ "single_word": false
14
+ },
15
+ "eos_token": {
16
+ "content": "</s>",
17
+ "lstrip": false,
18
+ "normalized": false,
19
+ "rstrip": false,
20
+ "single_word": false
21
+ },
22
+ "pad_token": "</s>",
23
+ "unk_token": {
24
+ "content": "<unk>",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ }
30
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
3
+ size 500058
tokenizer_config.json ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "32007": {
30
+ "content": "▁<PRE>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "32008": {
38
+ "content": "▁<SUF>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "32009": {
46
+ "content": "▁<MID>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "32010": {
54
+ "content": "▁<EOT>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ }
61
+ },
62
+ "additional_special_tokens": [
63
+ "▁<PRE>",
64
+ "▁<MID>",
65
+ "▁<SUF>",
66
+ "▁<EOT>"
67
+ ],
68
+ "bos_token": "<s>",
69
+ "clean_up_tokenization_spaces": false,
70
+ "eos_token": "</s>",
71
+ "eot_token": "▁<EOT>",
72
+ "extra_special_tokens": {},
73
+ "fill_token": "<FILL_ME>",
74
+ "legacy": null,
75
+ "middle_token": "▁<MID>",
76
+ "model_max_length": 1000000000000000019884624838656,
77
+ "pad_token": "</s>",
78
+ "prefix_token": "▁<PRE>",
79
+ "sp_model_kwargs": {},
80
+ "suffix_token": "▁<SUF>",
81
+ "tokenizer_class": "CodeLlamaTokenizer",
82
+ "unk_token": "<unk>",
83
+ "use_default_system_prompt": false
84
+ }
trainer_state.json ADDED
@@ -0,0 +1,934 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 0.719208870242733,
6
+ "eval_steps": 500,
7
+ "global_step": 900,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "entropy": 1.3359488248825073,
14
+ "epoch": 0.0079912096693637,
15
+ "grad_norm": 13.5,
16
+ "learning_rate": 0.00018,
17
+ "loss": 1.1391,
18
+ "mean_token_accuracy": 0.7321531124413013,
19
+ "num_tokens": 17863.0,
20
+ "step": 10
21
+ },
22
+ {
23
+ "entropy": 0.8153514951467514,
24
+ "epoch": 0.0159824193387274,
25
+ "grad_norm": 0.357421875,
26
+ "learning_rate": 0.00019855072463768116,
27
+ "loss": 0.735,
28
+ "mean_token_accuracy": 0.806717099994421,
29
+ "num_tokens": 35538.0,
30
+ "step": 20
31
+ },
32
+ {
33
+ "entropy": 0.7226301684975625,
34
+ "epoch": 0.0239736290080911,
35
+ "grad_norm": 0.27734375,
36
+ "learning_rate": 0.00019694041867954914,
37
+ "loss": 0.6906,
38
+ "mean_token_accuracy": 0.8121421404182911,
39
+ "num_tokens": 52898.0,
40
+ "step": 30
41
+ },
42
+ {
43
+ "entropy": 0.7096233293414116,
44
+ "epoch": 0.0319648386774548,
45
+ "grad_norm": 0.408203125,
46
+ "learning_rate": 0.00019533011272141707,
47
+ "loss": 0.6794,
48
+ "mean_token_accuracy": 0.8093454599380493,
49
+ "num_tokens": 71120.0,
50
+ "step": 40
51
+ },
52
+ {
53
+ "entropy": 0.6432753155007959,
54
+ "epoch": 0.0399560483468185,
55
+ "grad_norm": 0.29296875,
56
+ "learning_rate": 0.00019371980676328502,
57
+ "loss": 0.5778,
58
+ "mean_token_accuracy": 0.8227488771080971,
59
+ "num_tokens": 89183.0,
60
+ "step": 50
61
+ },
62
+ {
63
+ "entropy": 0.6528786711394787,
64
+ "epoch": 0.0479472580161822,
65
+ "grad_norm": 0.19921875,
66
+ "learning_rate": 0.000192109500805153,
67
+ "loss": 0.6056,
68
+ "mean_token_accuracy": 0.8218209922313691,
69
+ "num_tokens": 108013.0,
70
+ "step": 60
71
+ },
72
+ {
73
+ "entropy": 0.6535129006952047,
74
+ "epoch": 0.055938467685545896,
75
+ "grad_norm": 0.2236328125,
76
+ "learning_rate": 0.00019049919484702096,
77
+ "loss": 0.5954,
78
+ "mean_token_accuracy": 0.8255642831325531,
79
+ "num_tokens": 126649.0,
80
+ "step": 70
81
+ },
82
+ {
83
+ "entropy": 0.6079864472150802,
84
+ "epoch": 0.0639296773549096,
85
+ "grad_norm": 0.2001953125,
86
+ "learning_rate": 0.00018888888888888888,
87
+ "loss": 0.5911,
88
+ "mean_token_accuracy": 0.8231404431164264,
89
+ "num_tokens": 144182.0,
90
+ "step": 80
91
+ },
92
+ {
93
+ "entropy": 0.6695162910968065,
94
+ "epoch": 0.0719208870242733,
95
+ "grad_norm": 0.1962890625,
96
+ "learning_rate": 0.00018727858293075687,
97
+ "loss": 0.6312,
98
+ "mean_token_accuracy": 0.8185268670320511,
99
+ "num_tokens": 163634.0,
100
+ "step": 90
101
+ },
102
+ {
103
+ "entropy": 0.6382982328534126,
104
+ "epoch": 0.079912096693637,
105
+ "grad_norm": 0.2109375,
106
+ "learning_rate": 0.00018566827697262482,
107
+ "loss": 0.5965,
108
+ "mean_token_accuracy": 0.8219615206122398,
109
+ "num_tokens": 182899.0,
110
+ "step": 100
111
+ },
112
+ {
113
+ "entropy": 0.615644377656281,
114
+ "epoch": 0.0879033063630007,
115
+ "grad_norm": 0.17578125,
116
+ "learning_rate": 0.00018405797101449275,
117
+ "loss": 0.555,
118
+ "mean_token_accuracy": 0.8339135125279427,
119
+ "num_tokens": 201540.0,
120
+ "step": 110
121
+ },
122
+ {
123
+ "entropy": 0.6227292243391276,
124
+ "epoch": 0.0958945160323644,
125
+ "grad_norm": 0.2392578125,
126
+ "learning_rate": 0.00018244766505636073,
127
+ "loss": 0.5958,
128
+ "mean_token_accuracy": 0.822028624266386,
129
+ "num_tokens": 220163.0,
130
+ "step": 120
131
+ },
132
+ {
133
+ "entropy": 0.6280987083911895,
134
+ "epoch": 0.1038857257017281,
135
+ "grad_norm": 0.2177734375,
136
+ "learning_rate": 0.00018083735909822868,
137
+ "loss": 0.5827,
138
+ "mean_token_accuracy": 0.8300345286726951,
139
+ "num_tokens": 237989.0,
140
+ "step": 130
141
+ },
142
+ {
143
+ "entropy": 0.6323467470705509,
144
+ "epoch": 0.11187693537109179,
145
+ "grad_norm": 0.154296875,
146
+ "learning_rate": 0.00017922705314009664,
147
+ "loss": 0.5986,
148
+ "mean_token_accuracy": 0.8197977431118488,
149
+ "num_tokens": 256250.0,
150
+ "step": 140
151
+ },
152
+ {
153
+ "entropy": 0.6162901744246483,
154
+ "epoch": 0.1198681450404555,
155
+ "grad_norm": 0.1552734375,
156
+ "learning_rate": 0.00017761674718196456,
157
+ "loss": 0.5769,
158
+ "mean_token_accuracy": 0.8255695670843124,
159
+ "num_tokens": 274386.0,
160
+ "step": 150
161
+ },
162
+ {
163
+ "entropy": 0.6158512964844703,
164
+ "epoch": 0.1278593547098192,
165
+ "grad_norm": 0.203125,
166
+ "learning_rate": 0.00017600644122383254,
167
+ "loss": 0.5713,
168
+ "mean_token_accuracy": 0.8270042009651661,
169
+ "num_tokens": 292835.0,
170
+ "step": 160
171
+ },
172
+ {
173
+ "entropy": 0.6406407546252012,
174
+ "epoch": 0.1358505643791829,
175
+ "grad_norm": 0.2119140625,
176
+ "learning_rate": 0.0001743961352657005,
177
+ "loss": 0.6104,
178
+ "mean_token_accuracy": 0.8200316116213798,
179
+ "num_tokens": 310392.0,
180
+ "step": 170
181
+ },
182
+ {
183
+ "entropy": 0.6069310043007136,
184
+ "epoch": 0.1438417740485466,
185
+ "grad_norm": 0.1640625,
186
+ "learning_rate": 0.00017278582930756842,
187
+ "loss": 0.5624,
188
+ "mean_token_accuracy": 0.8317995510995388,
189
+ "num_tokens": 331305.0,
190
+ "step": 180
191
+ },
192
+ {
193
+ "entropy": 0.6235411781817675,
194
+ "epoch": 0.1518329837179103,
195
+ "grad_norm": 0.1640625,
196
+ "learning_rate": 0.0001711755233494364,
197
+ "loss": 0.5852,
198
+ "mean_token_accuracy": 0.8278815999627114,
199
+ "num_tokens": 349604.0,
200
+ "step": 190
201
+ },
202
+ {
203
+ "entropy": 0.6172796195372939,
204
+ "epoch": 0.159824193387274,
205
+ "grad_norm": 0.1669921875,
206
+ "learning_rate": 0.00016956521739130436,
207
+ "loss": 0.5764,
208
+ "mean_token_accuracy": 0.8313593462109565,
209
+ "num_tokens": 367876.0,
210
+ "step": 200
211
+ },
212
+ {
213
+ "entropy": 0.6155283484607935,
214
+ "epoch": 0.1678154030566377,
215
+ "grad_norm": 0.1865234375,
216
+ "learning_rate": 0.00016795491143317231,
217
+ "loss": 0.5773,
218
+ "mean_token_accuracy": 0.8269082359969616,
219
+ "num_tokens": 385573.0,
220
+ "step": 210
221
+ },
222
+ {
223
+ "entropy": 0.6083606427535415,
224
+ "epoch": 0.1758066127260014,
225
+ "grad_norm": 0.154296875,
226
+ "learning_rate": 0.00016634460547504027,
227
+ "loss": 0.5704,
228
+ "mean_token_accuracy": 0.8263973362743855,
229
+ "num_tokens": 404851.0,
230
+ "step": 220
231
+ },
232
+ {
233
+ "entropy": 0.6131238225847483,
234
+ "epoch": 0.1837978223953651,
235
+ "grad_norm": 0.20703125,
236
+ "learning_rate": 0.00016473429951690822,
237
+ "loss": 0.5817,
238
+ "mean_token_accuracy": 0.8245558224618434,
239
+ "num_tokens": 422809.0,
240
+ "step": 230
241
+ },
242
+ {
243
+ "entropy": 0.6223553754389286,
244
+ "epoch": 0.1917890320647288,
245
+ "grad_norm": 0.234375,
246
+ "learning_rate": 0.00016312399355877618,
247
+ "loss": 0.5871,
248
+ "mean_token_accuracy": 0.8232570059597493,
249
+ "num_tokens": 439086.0,
250
+ "step": 240
251
+ },
252
+ {
253
+ "entropy": 0.6230555597692728,
254
+ "epoch": 0.1997802417340925,
255
+ "grad_norm": 0.171875,
256
+ "learning_rate": 0.00016151368760064413,
257
+ "loss": 0.5751,
258
+ "mean_token_accuracy": 0.8289580881595612,
259
+ "num_tokens": 457157.0,
260
+ "step": 250
261
+ },
262
+ {
263
+ "entropy": 0.5794363841414452,
264
+ "epoch": 0.2077714514034562,
265
+ "grad_norm": 0.2294921875,
266
+ "learning_rate": 0.00015990338164251208,
267
+ "loss": 0.5627,
268
+ "mean_token_accuracy": 0.8365659207105637,
269
+ "num_tokens": 474701.0,
270
+ "step": 260
271
+ },
272
+ {
273
+ "entropy": 0.5860258772969246,
274
+ "epoch": 0.2157626610728199,
275
+ "grad_norm": 0.1484375,
276
+ "learning_rate": 0.00015829307568438004,
277
+ "loss": 0.5363,
278
+ "mean_token_accuracy": 0.8401569269597531,
279
+ "num_tokens": 495405.0,
280
+ "step": 270
281
+ },
282
+ {
283
+ "entropy": 0.581408916413784,
284
+ "epoch": 0.22375387074218359,
285
+ "grad_norm": 0.205078125,
286
+ "learning_rate": 0.000156682769726248,
287
+ "loss": 0.5593,
288
+ "mean_token_accuracy": 0.8319723285734654,
289
+ "num_tokens": 512629.0,
290
+ "step": 280
291
+ },
292
+ {
293
+ "entropy": 0.5774631313979626,
294
+ "epoch": 0.2317450804115473,
295
+ "grad_norm": 0.171875,
296
+ "learning_rate": 0.00015507246376811595,
297
+ "loss": 0.5445,
298
+ "mean_token_accuracy": 0.8400227598845958,
299
+ "num_tokens": 531652.0,
300
+ "step": 290
301
+ },
302
+ {
303
+ "entropy": 0.5888700131326914,
304
+ "epoch": 0.239736290080911,
305
+ "grad_norm": 0.1884765625,
306
+ "learning_rate": 0.0001534621578099839,
307
+ "loss": 0.5475,
308
+ "mean_token_accuracy": 0.8398719631135464,
309
+ "num_tokens": 551807.0,
310
+ "step": 300
311
+ },
312
+ {
313
+ "entropy": 0.6303706657141447,
314
+ "epoch": 0.2477274997502747,
315
+ "grad_norm": 0.185546875,
316
+ "learning_rate": 0.00015185185185185185,
317
+ "loss": 0.5994,
318
+ "mean_token_accuracy": 0.8221785329282284,
319
+ "num_tokens": 570173.0,
320
+ "step": 310
321
+ },
322
+ {
323
+ "entropy": 0.591961058229208,
324
+ "epoch": 0.2557187094196384,
325
+ "grad_norm": 0.1708984375,
326
+ "learning_rate": 0.0001502415458937198,
327
+ "loss": 0.5588,
328
+ "mean_token_accuracy": 0.8339079335331917,
329
+ "num_tokens": 587517.0,
330
+ "step": 320
331
+ },
332
+ {
333
+ "entropy": 0.6203833676874637,
334
+ "epoch": 0.2637099190890021,
335
+ "grad_norm": 0.158203125,
336
+ "learning_rate": 0.00014863123993558776,
337
+ "loss": 0.5993,
338
+ "mean_token_accuracy": 0.8254540674388409,
339
+ "num_tokens": 605533.0,
340
+ "step": 330
341
+ },
342
+ {
343
+ "entropy": 0.5948904637247324,
344
+ "epoch": 0.2717011287583658,
345
+ "grad_norm": 0.1689453125,
346
+ "learning_rate": 0.00014702093397745574,
347
+ "loss": 0.5386,
348
+ "mean_token_accuracy": 0.835470549017191,
349
+ "num_tokens": 623145.0,
350
+ "step": 340
351
+ },
352
+ {
353
+ "entropy": 0.5892129261046648,
354
+ "epoch": 0.2796923384277295,
355
+ "grad_norm": 0.2041015625,
356
+ "learning_rate": 0.00014541062801932367,
357
+ "loss": 0.5445,
358
+ "mean_token_accuracy": 0.8327487081289291,
359
+ "num_tokens": 642429.0,
360
+ "step": 350
361
+ },
362
+ {
363
+ "entropy": 0.58230458535254,
364
+ "epoch": 0.2876835480970932,
365
+ "grad_norm": 0.1748046875,
366
+ "learning_rate": 0.00014380032206119162,
367
+ "loss": 0.5458,
368
+ "mean_token_accuracy": 0.8369288526475429,
369
+ "num_tokens": 660595.0,
370
+ "step": 360
371
+ },
372
+ {
373
+ "entropy": 0.5953514769673347,
374
+ "epoch": 0.2956747577664569,
375
+ "grad_norm": 0.1494140625,
376
+ "learning_rate": 0.0001421900161030596,
377
+ "loss": 0.5564,
378
+ "mean_token_accuracy": 0.8314083501696586,
379
+ "num_tokens": 680301.0,
380
+ "step": 370
381
+ },
382
+ {
383
+ "entropy": 0.6272314839065075,
384
+ "epoch": 0.3036659674358206,
385
+ "grad_norm": 0.189453125,
386
+ "learning_rate": 0.00014057971014492753,
387
+ "loss": 0.5879,
388
+ "mean_token_accuracy": 0.8269149273633957,
389
+ "num_tokens": 698836.0,
390
+ "step": 380
391
+ },
392
+ {
393
+ "entropy": 0.5974850662052631,
394
+ "epoch": 0.3116571771051843,
395
+ "grad_norm": 0.1875,
396
+ "learning_rate": 0.0001389694041867955,
397
+ "loss": 0.5567,
398
+ "mean_token_accuracy": 0.8330555327236653,
399
+ "num_tokens": 717301.0,
400
+ "step": 390
401
+ },
402
+ {
403
+ "entropy": 0.610439121723175,
404
+ "epoch": 0.319648386774548,
405
+ "grad_norm": 0.1943359375,
406
+ "learning_rate": 0.00013735909822866347,
407
+ "loss": 0.5798,
408
+ "mean_token_accuracy": 0.8273908801376819,
409
+ "num_tokens": 735623.0,
410
+ "step": 400
411
+ },
412
+ {
413
+ "entropy": 0.6218720726668835,
414
+ "epoch": 0.3276395964439117,
415
+ "grad_norm": 0.1689453125,
416
+ "learning_rate": 0.00013574879227053142,
417
+ "loss": 0.5681,
418
+ "mean_token_accuracy": 0.8264160886406898,
419
+ "num_tokens": 754095.0,
420
+ "step": 410
421
+ },
422
+ {
423
+ "entropy": 0.5961160399019718,
424
+ "epoch": 0.3356308061132754,
425
+ "grad_norm": 0.130859375,
426
+ "learning_rate": 0.00013413848631239935,
427
+ "loss": 0.5649,
428
+ "mean_token_accuracy": 0.8278753645718098,
429
+ "num_tokens": 772932.0,
430
+ "step": 420
431
+ },
432
+ {
433
+ "entropy": 0.5970222994685173,
434
+ "epoch": 0.3436220157826391,
435
+ "grad_norm": 0.1552734375,
436
+ "learning_rate": 0.0001325281803542673,
437
+ "loss": 0.5717,
438
+ "mean_token_accuracy": 0.8289826177060604,
439
+ "num_tokens": 791954.0,
440
+ "step": 430
441
+ },
442
+ {
443
+ "entropy": 0.5869237255305052,
444
+ "epoch": 0.3516132254520028,
445
+ "grad_norm": 0.23828125,
446
+ "learning_rate": 0.00013091787439613528,
447
+ "loss": 0.5424,
448
+ "mean_token_accuracy": 0.8353226915001869,
449
+ "num_tokens": 810372.0,
450
+ "step": 440
451
+ },
452
+ {
453
+ "entropy": 0.6047268303111195,
454
+ "epoch": 0.3596044351213665,
455
+ "grad_norm": 0.16015625,
456
+ "learning_rate": 0.0001293075684380032,
457
+ "loss": 0.5816,
458
+ "mean_token_accuracy": 0.8292522899806499,
459
+ "num_tokens": 828031.0,
460
+ "step": 450
461
+ },
462
+ {
463
+ "entropy": 0.6398113902658225,
464
+ "epoch": 0.3675956447907302,
465
+ "grad_norm": 0.193359375,
466
+ "learning_rate": 0.00012769726247987117,
467
+ "loss": 0.587,
468
+ "mean_token_accuracy": 0.8254243724048138,
469
+ "num_tokens": 844965.0,
470
+ "step": 460
471
+ },
472
+ {
473
+ "entropy": 0.5699722157791257,
474
+ "epoch": 0.3755868544600939,
475
+ "grad_norm": 0.150390625,
476
+ "learning_rate": 0.00012608695652173915,
477
+ "loss": 0.5302,
478
+ "mean_token_accuracy": 0.8379433415830135,
479
+ "num_tokens": 864068.0,
480
+ "step": 470
481
+ },
482
+ {
483
+ "entropy": 0.6004057168960572,
484
+ "epoch": 0.3835780641294576,
485
+ "grad_norm": 0.1689453125,
486
+ "learning_rate": 0.0001244766505636071,
487
+ "loss": 0.5735,
488
+ "mean_token_accuracy": 0.8319472163915634,
489
+ "num_tokens": 882516.0,
490
+ "step": 480
491
+ },
492
+ {
493
+ "entropy": 0.612379564717412,
494
+ "epoch": 0.3915692737988213,
495
+ "grad_norm": 0.17578125,
496
+ "learning_rate": 0.00012286634460547503,
497
+ "loss": 0.5605,
498
+ "mean_token_accuracy": 0.8312513306736946,
499
+ "num_tokens": 901332.0,
500
+ "step": 490
501
+ },
502
+ {
503
+ "entropy": 0.5999802689999342,
504
+ "epoch": 0.399560483468185,
505
+ "grad_norm": 0.2236328125,
506
+ "learning_rate": 0.00012125603864734301,
507
+ "loss": 0.5844,
508
+ "mean_token_accuracy": 0.8295043386518955,
509
+ "num_tokens": 918902.0,
510
+ "step": 500
511
+ },
512
+ {
513
+ "entropy": 0.6438330963253975,
514
+ "epoch": 0.4075516931375487,
515
+ "grad_norm": 0.181640625,
516
+ "learning_rate": 0.00011964573268921095,
517
+ "loss": 0.6039,
518
+ "mean_token_accuracy": 0.8217731453478336,
519
+ "num_tokens": 937381.0,
520
+ "step": 510
521
+ },
522
+ {
523
+ "entropy": 0.557589478418231,
524
+ "epoch": 0.4155429028069124,
525
+ "grad_norm": 0.1748046875,
526
+ "learning_rate": 0.0001180354267310789,
527
+ "loss": 0.5347,
528
+ "mean_token_accuracy": 0.8419624336063862,
529
+ "num_tokens": 956408.0,
530
+ "step": 520
531
+ },
532
+ {
533
+ "entropy": 0.5831106752157211,
534
+ "epoch": 0.4235341124762761,
535
+ "grad_norm": 0.15625,
536
+ "learning_rate": 0.00011642512077294687,
537
+ "loss": 0.5566,
538
+ "mean_token_accuracy": 0.8344054028391839,
539
+ "num_tokens": 974727.0,
540
+ "step": 530
541
+ },
542
+ {
543
+ "entropy": 0.6096597962081433,
544
+ "epoch": 0.4315253221456398,
545
+ "grad_norm": 0.16015625,
546
+ "learning_rate": 0.00011481481481481482,
547
+ "loss": 0.5906,
548
+ "mean_token_accuracy": 0.8249844819307327,
549
+ "num_tokens": 992039.0,
550
+ "step": 540
551
+ },
552
+ {
553
+ "entropy": 0.6296380385756493,
554
+ "epoch": 0.4395165318150035,
555
+ "grad_norm": 0.185546875,
556
+ "learning_rate": 0.00011320450885668277,
557
+ "loss": 0.5774,
558
+ "mean_token_accuracy": 0.8290597923099995,
559
+ "num_tokens": 1010746.0,
560
+ "step": 550
561
+ },
562
+ {
563
+ "entropy": 0.5989726323634386,
564
+ "epoch": 0.44750774148436717,
565
+ "grad_norm": 0.1552734375,
566
+ "learning_rate": 0.00011159420289855073,
567
+ "loss": 0.5668,
568
+ "mean_token_accuracy": 0.8317835494875908,
569
+ "num_tokens": 1029302.0,
570
+ "step": 560
571
+ },
572
+ {
573
+ "entropy": 0.5985535632818937,
574
+ "epoch": 0.4554989511537309,
575
+ "grad_norm": 0.1533203125,
576
+ "learning_rate": 0.00010998389694041869,
577
+ "loss": 0.5927,
578
+ "mean_token_accuracy": 0.8251331336796284,
579
+ "num_tokens": 1047787.0,
580
+ "step": 570
581
+ },
582
+ {
583
+ "entropy": 0.5919383157044649,
584
+ "epoch": 0.4634901608230946,
585
+ "grad_norm": 0.140625,
586
+ "learning_rate": 0.00010837359098228663,
587
+ "loss": 0.5584,
588
+ "mean_token_accuracy": 0.8338681124150753,
589
+ "num_tokens": 1067471.0,
590
+ "step": 580
591
+ },
592
+ {
593
+ "entropy": 0.5655450899153948,
594
+ "epoch": 0.4714813704924583,
595
+ "grad_norm": 0.146484375,
596
+ "learning_rate": 0.00010676328502415461,
597
+ "loss": 0.5343,
598
+ "mean_token_accuracy": 0.8383485890924931,
599
+ "num_tokens": 1086046.0,
600
+ "step": 590
601
+ },
602
+ {
603
+ "entropy": 0.616737426072359,
604
+ "epoch": 0.479472580161822,
605
+ "grad_norm": 0.173828125,
606
+ "learning_rate": 0.00010515297906602255,
607
+ "loss": 0.5908,
608
+ "mean_token_accuracy": 0.8193590499460697,
609
+ "num_tokens": 1103227.0,
610
+ "step": 600
611
+ },
612
+ {
613
+ "entropy": 0.5877503883093596,
614
+ "epoch": 0.4874637898311857,
615
+ "grad_norm": 0.16796875,
616
+ "learning_rate": 0.0001035426731078905,
617
+ "loss": 0.5505,
618
+ "mean_token_accuracy": 0.8355500593781471,
619
+ "num_tokens": 1121994.0,
620
+ "step": 610
621
+ },
622
+ {
623
+ "entropy": 0.5908785469830036,
624
+ "epoch": 0.4954549995005494,
625
+ "grad_norm": 0.2255859375,
626
+ "learning_rate": 0.00010193236714975847,
627
+ "loss": 0.5794,
628
+ "mean_token_accuracy": 0.8315194040536881,
629
+ "num_tokens": 1139965.0,
630
+ "step": 620
631
+ },
632
+ {
633
+ "entropy": 0.6211531057953834,
634
+ "epoch": 0.5034462091699131,
635
+ "grad_norm": 0.134765625,
636
+ "learning_rate": 0.00010032206119162641,
637
+ "loss": 0.5664,
638
+ "mean_token_accuracy": 0.8258850328624249,
639
+ "num_tokens": 1159075.0,
640
+ "step": 630
641
+ },
642
+ {
643
+ "entropy": 0.5950863931328059,
644
+ "epoch": 0.5114374188392768,
645
+ "grad_norm": 0.1630859375,
646
+ "learning_rate": 9.871175523349438e-05,
647
+ "loss": 0.5497,
648
+ "mean_token_accuracy": 0.8346662126481533,
649
+ "num_tokens": 1176494.0,
650
+ "step": 640
651
+ },
652
+ {
653
+ "entropy": 0.5760080838575959,
654
+ "epoch": 0.5194286285086405,
655
+ "grad_norm": 0.23828125,
656
+ "learning_rate": 9.710144927536232e-05,
657
+ "loss": 0.5632,
658
+ "mean_token_accuracy": 0.8364547491073608,
659
+ "num_tokens": 1195371.0,
660
+ "step": 650
661
+ },
662
+ {
663
+ "entropy": 0.5897768154740334,
664
+ "epoch": 0.5274198381780042,
665
+ "grad_norm": 0.150390625,
666
+ "learning_rate": 9.549114331723029e-05,
667
+ "loss": 0.5611,
668
+ "mean_token_accuracy": 0.8353584706783295,
669
+ "num_tokens": 1215474.0,
670
+ "step": 660
671
+ },
672
+ {
673
+ "entropy": 0.6259935267269612,
674
+ "epoch": 0.5354110478473679,
675
+ "grad_norm": 0.19921875,
676
+ "learning_rate": 9.388083735909823e-05,
677
+ "loss": 0.5834,
678
+ "mean_token_accuracy": 0.8251566261053085,
679
+ "num_tokens": 1233066.0,
680
+ "step": 670
681
+ },
682
+ {
683
+ "entropy": 0.5858545243740082,
684
+ "epoch": 0.5434022575167315,
685
+ "grad_norm": 0.2080078125,
686
+ "learning_rate": 9.227053140096618e-05,
687
+ "loss": 0.5709,
688
+ "mean_token_accuracy": 0.8273489251732826,
689
+ "num_tokens": 1249355.0,
690
+ "step": 680
691
+ },
692
+ {
693
+ "entropy": 0.6020776845514775,
694
+ "epoch": 0.5513934671860953,
695
+ "grad_norm": 0.171875,
696
+ "learning_rate": 9.066022544283415e-05,
697
+ "loss": 0.5657,
698
+ "mean_token_accuracy": 0.8260138787329196,
699
+ "num_tokens": 1267301.0,
700
+ "step": 690
701
+ },
702
+ {
703
+ "entropy": 0.596510236337781,
704
+ "epoch": 0.559384676855459,
705
+ "grad_norm": 0.154296875,
706
+ "learning_rate": 8.904991948470209e-05,
707
+ "loss": 0.5557,
708
+ "mean_token_accuracy": 0.834468311816454,
709
+ "num_tokens": 1285467.0,
710
+ "step": 700
711
+ },
712
+ {
713
+ "entropy": 0.5882966015487909,
714
+ "epoch": 0.5673758865248227,
715
+ "grad_norm": 0.166015625,
716
+ "learning_rate": 8.743961352657006e-05,
717
+ "loss": 0.5423,
718
+ "mean_token_accuracy": 0.8352835536003113,
719
+ "num_tokens": 1304357.0,
720
+ "step": 710
721
+ },
722
+ {
723
+ "entropy": 0.6191790480166673,
724
+ "epoch": 0.5753670961941864,
725
+ "grad_norm": 0.1533203125,
726
+ "learning_rate": 8.582930756843801e-05,
727
+ "loss": 0.5759,
728
+ "mean_token_accuracy": 0.8274984866380691,
729
+ "num_tokens": 1321602.0,
730
+ "step": 720
731
+ },
732
+ {
733
+ "entropy": 0.6024752855300903,
734
+ "epoch": 0.5833583058635501,
735
+ "grad_norm": 0.2001953125,
736
+ "learning_rate": 8.421900161030597e-05,
737
+ "loss": 0.5638,
738
+ "mean_token_accuracy": 0.8288030169904232,
739
+ "num_tokens": 1340012.0,
740
+ "step": 730
741
+ },
742
+ {
743
+ "entropy": 0.5633068412542344,
744
+ "epoch": 0.5913495155329138,
745
+ "grad_norm": 0.1796875,
746
+ "learning_rate": 8.260869565217392e-05,
747
+ "loss": 0.5262,
748
+ "mean_token_accuracy": 0.8409125037491322,
749
+ "num_tokens": 1358549.0,
750
+ "step": 740
751
+ },
752
+ {
753
+ "entropy": 0.6121923718601465,
754
+ "epoch": 0.5993407252022775,
755
+ "grad_norm": 0.1640625,
756
+ "learning_rate": 8.099838969404187e-05,
757
+ "loss": 0.5782,
758
+ "mean_token_accuracy": 0.8247248627245426,
759
+ "num_tokens": 1376295.0,
760
+ "step": 750
761
+ },
762
+ {
763
+ "entropy": 0.5850671246647835,
764
+ "epoch": 0.6073319348716412,
765
+ "grad_norm": 0.12255859375,
766
+ "learning_rate": 7.938808373590983e-05,
767
+ "loss": 0.5481,
768
+ "mean_token_accuracy": 0.8378213487565518,
769
+ "num_tokens": 1396825.0,
770
+ "step": 760
771
+ },
772
+ {
773
+ "entropy": 0.6004991352558136,
774
+ "epoch": 0.6153231445410049,
775
+ "grad_norm": 0.1484375,
776
+ "learning_rate": 7.777777777777778e-05,
777
+ "loss": 0.5697,
778
+ "mean_token_accuracy": 0.8314851686358452,
779
+ "num_tokens": 1415779.0,
780
+ "step": 770
781
+ },
782
+ {
783
+ "entropy": 0.615888693742454,
784
+ "epoch": 0.6233143542103686,
785
+ "grad_norm": 0.1494140625,
786
+ "learning_rate": 7.616747181964574e-05,
787
+ "loss": 0.586,
788
+ "mean_token_accuracy": 0.8290720954537392,
789
+ "num_tokens": 1433844.0,
790
+ "step": 780
791
+ },
792
+ {
793
+ "entropy": 0.631605738401413,
794
+ "epoch": 0.6313055638797322,
795
+ "grad_norm": 0.1787109375,
796
+ "learning_rate": 7.455716586151369e-05,
797
+ "loss": 0.5896,
798
+ "mean_token_accuracy": 0.823421498388052,
799
+ "num_tokens": 1452173.0,
800
+ "step": 790
801
+ },
802
+ {
803
+ "entropy": 0.5806491080671549,
804
+ "epoch": 0.639296773549096,
805
+ "grad_norm": 0.1767578125,
806
+ "learning_rate": 7.294685990338164e-05,
807
+ "loss": 0.5541,
808
+ "mean_token_accuracy": 0.8376387834548951,
809
+ "num_tokens": 1469089.0,
810
+ "step": 800
811
+ },
812
+ {
813
+ "entropy": 0.5787392556667328,
814
+ "epoch": 0.6472879832184597,
815
+ "grad_norm": 0.2734375,
816
+ "learning_rate": 7.13365539452496e-05,
817
+ "loss": 0.5344,
818
+ "mean_token_accuracy": 0.832699004560709,
819
+ "num_tokens": 1488541.0,
820
+ "step": 810
821
+ },
822
+ {
823
+ "entropy": 0.5935858219861985,
824
+ "epoch": 0.6552791928878234,
825
+ "grad_norm": 0.1435546875,
826
+ "learning_rate": 6.972624798711755e-05,
827
+ "loss": 0.549,
828
+ "mean_token_accuracy": 0.8358408592641353,
829
+ "num_tokens": 1506966.0,
830
+ "step": 820
831
+ },
832
+ {
833
+ "entropy": 0.6146302495151759,
834
+ "epoch": 0.663270402557187,
835
+ "grad_norm": 0.15234375,
836
+ "learning_rate": 6.811594202898552e-05,
837
+ "loss": 0.5794,
838
+ "mean_token_accuracy": 0.8260477609932423,
839
+ "num_tokens": 1526428.0,
840
+ "step": 830
841
+ },
842
+ {
843
+ "entropy": 0.6146373618394136,
844
+ "epoch": 0.6712616122265508,
845
+ "grad_norm": 0.169921875,
846
+ "learning_rate": 6.650563607085346e-05,
847
+ "loss": 0.5917,
848
+ "mean_token_accuracy": 0.8253330059349537,
849
+ "num_tokens": 1543859.0,
850
+ "step": 840
851
+ },
852
+ {
853
+ "entropy": 0.5822377149015665,
854
+ "epoch": 0.6792528218959145,
855
+ "grad_norm": 0.1962890625,
856
+ "learning_rate": 6.489533011272141e-05,
857
+ "loss": 0.5561,
858
+ "mean_token_accuracy": 0.8367624327540397,
859
+ "num_tokens": 1562062.0,
860
+ "step": 850
861
+ },
862
+ {
863
+ "entropy": 0.5773209661245347,
864
+ "epoch": 0.6872440315652782,
865
+ "grad_norm": 0.1650390625,
866
+ "learning_rate": 6.328502415458938e-05,
867
+ "loss": 0.5144,
868
+ "mean_token_accuracy": 0.83621421828866,
869
+ "num_tokens": 1580374.0,
870
+ "step": 860
871
+ },
872
+ {
873
+ "entropy": 0.5891423657536506,
874
+ "epoch": 0.6952352412346419,
875
+ "grad_norm": 0.18359375,
876
+ "learning_rate": 6.167471819645732e-05,
877
+ "loss": 0.5766,
878
+ "mean_token_accuracy": 0.8288635179400444,
879
+ "num_tokens": 1598383.0,
880
+ "step": 870
881
+ },
882
+ {
883
+ "entropy": 0.5979194710031152,
884
+ "epoch": 0.7032264509040056,
885
+ "grad_norm": 0.15234375,
886
+ "learning_rate": 6.006441223832528e-05,
887
+ "loss": 0.5452,
888
+ "mean_token_accuracy": 0.8346437945961952,
889
+ "num_tokens": 1617322.0,
890
+ "step": 880
891
+ },
892
+ {
893
+ "entropy": 0.6381862349808216,
894
+ "epoch": 0.7112176605733693,
895
+ "grad_norm": 0.173828125,
896
+ "learning_rate": 5.8454106280193244e-05,
897
+ "loss": 0.6008,
898
+ "mean_token_accuracy": 0.8242271035909653,
899
+ "num_tokens": 1633941.0,
900
+ "step": 890
901
+ },
902
+ {
903
+ "entropy": 0.5802713014185429,
904
+ "epoch": 0.719208870242733,
905
+ "grad_norm": 0.15625,
906
+ "learning_rate": 5.684380032206119e-05,
907
+ "loss": 0.5462,
908
+ "mean_token_accuracy": 0.8342008836567402,
909
+ "num_tokens": 1651765.0,
910
+ "step": 900
911
+ }
912
+ ],
913
+ "logging_steps": 10,
914
+ "max_steps": 1252,
915
+ "num_input_tokens_seen": 0,
916
+ "num_train_epochs": 1,
917
+ "save_steps": 100,
918
+ "stateful_callbacks": {
919
+ "TrainerControl": {
920
+ "args": {
921
+ "should_epoch_stop": false,
922
+ "should_evaluate": false,
923
+ "should_log": false,
924
+ "should_save": true,
925
+ "should_training_stop": false
926
+ },
927
+ "attributes": {}
928
+ }
929
+ },
930
+ "total_flos": 8.51066844059566e+16,
931
+ "train_batch_size": 2,
932
+ "trial_name": null,
933
+ "trial_params": null
934
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8171513fb0ce0e4550964403bd08f3491e6f0320f0fb9d8af0af897607dfa40f
3
+ size 6289