diagonalge commited on
Commit
df1cea9
·
verified ·
1 Parent(s): 897a943

Migrated from latest commit: Upload task output e5439073-3144-4ed0-aa87-6f301d440db4

Browse files
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: diagonalge/Covenant72B
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": "diagonalge/Covenant72B",
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
+ "q_proj",
28
+ "down_proj",
29
+ "v_proj",
30
+ "k_proj",
31
+ "o_proj",
32
+ "gate_proj",
33
+ "up_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 sha256:4892ecf77014d44e0eda3c2af83fc44c8f5da1a6bf4a4bc65b134b63a0b495db
3
+ size 3313655720
loss.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ 856,1.2667760848999023
trainer_state.json ADDED
@@ -0,0 +1,1255 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.9953379953379953,
6
+ "eval_steps": 500,
7
+ "global_step": 856,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.011655011655011656,
14
+ "grad_norm": 5.380261825460372,
15
+ "learning_rate": 9.237540571428572e-06,
16
+ "loss": 4.2109,
17
+ "step": 5
18
+ },
19
+ {
20
+ "epoch": 0.023310023310023312,
21
+ "grad_norm": 1.4502882732797857,
22
+ "learning_rate": 2.0784466285714287e-05,
23
+ "loss": 3.9981,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.03496503496503497,
28
+ "grad_norm": 0.9652384253156429,
29
+ "learning_rate": 3.2331392000000005e-05,
30
+ "loss": 3.2711,
31
+ "step": 15
32
+ },
33
+ {
34
+ "epoch": 0.046620046620046623,
35
+ "grad_norm": 1.1395250787625393,
36
+ "learning_rate": 4.3878317714285716e-05,
37
+ "loss": 2.6312,
38
+ "step": 20
39
+ },
40
+ {
41
+ "epoch": 0.05827505827505827,
42
+ "grad_norm": 3.4845160401616764,
43
+ "learning_rate": 5.542524342857144e-05,
44
+ "loss": 2.1284,
45
+ "step": 25
46
+ },
47
+ {
48
+ "epoch": 0.06993006993006994,
49
+ "grad_norm": 1.9051485411146671,
50
+ "learning_rate": 6.697216914285716e-05,
51
+ "loss": 1.8294,
52
+ "step": 30
53
+ },
54
+ {
55
+ "epoch": 0.08158508158508158,
56
+ "grad_norm": 0.33187533324621077,
57
+ "learning_rate": 7.851909485714286e-05,
58
+ "loss": 1.7266,
59
+ "step": 35
60
+ },
61
+ {
62
+ "epoch": 0.09324009324009325,
63
+ "grad_norm": 0.44248932276377023,
64
+ "learning_rate": 8.082695323179129e-05,
65
+ "loss": 1.7283,
66
+ "step": 40
67
+ },
68
+ {
69
+ "epoch": 0.1048951048951049,
70
+ "grad_norm": 1.2160485145535014,
71
+ "learning_rate": 8.082075099954982e-05,
72
+ "loss": 1.7117,
73
+ "step": 45
74
+ },
75
+ {
76
+ "epoch": 0.11655011655011654,
77
+ "grad_norm": 65.29684577693374,
78
+ "learning_rate": 8.080977885578941e-05,
79
+ "loss": 1.8952,
80
+ "step": 50
81
+ },
82
+ {
83
+ "epoch": 0.1282051282051282,
84
+ "grad_norm": 1.15546734315769,
85
+ "learning_rate": 8.079403852760764e-05,
86
+ "loss": 3.1909,
87
+ "step": 55
88
+ },
89
+ {
90
+ "epoch": 0.13986013986013987,
91
+ "grad_norm": 2.634452844296507,
92
+ "learning_rate": 8.077353249265015e-05,
93
+ "loss": 1.6638,
94
+ "step": 60
95
+ },
96
+ {
97
+ "epoch": 0.15151515151515152,
98
+ "grad_norm": 0.32202059804233973,
99
+ "learning_rate": 8.07482639787204e-05,
100
+ "loss": 1.6088,
101
+ "step": 65
102
+ },
103
+ {
104
+ "epoch": 0.16317016317016317,
105
+ "grad_norm": 0.3642353360782208,
106
+ "learning_rate": 8.071823696327185e-05,
107
+ "loss": 1.5268,
108
+ "step": 70
109
+ },
110
+ {
111
+ "epoch": 0.17482517482517482,
112
+ "grad_norm": 0.34692958418989034,
113
+ "learning_rate": 8.068345617278169e-05,
114
+ "loss": 1.5875,
115
+ "step": 75
116
+ },
117
+ {
118
+ "epoch": 0.1864801864801865,
119
+ "grad_norm": 38.12513649812565,
120
+ "learning_rate": 8.06439270820069e-05,
121
+ "loss": 1.7234,
122
+ "step": 80
123
+ },
124
+ {
125
+ "epoch": 0.19813519813519814,
126
+ "grad_norm": 0.3217004898392202,
127
+ "learning_rate": 8.059965591312254e-05,
128
+ "loss": 1.4259,
129
+ "step": 85
130
+ },
131
+ {
132
+ "epoch": 0.2097902097902098,
133
+ "grad_norm": 0.24719946255426536,
134
+ "learning_rate": 8.055064963474229e-05,
135
+ "loss": 1.4095,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 0.22144522144522144,
140
+ "grad_norm": 0.5042383844039631,
141
+ "learning_rate": 8.049691596082148e-05,
142
+ "loss": 1.6829,
143
+ "step": 95
144
+ },
145
+ {
146
+ "epoch": 0.2331002331002331,
147
+ "grad_norm": 0.2641927692422699,
148
+ "learning_rate": 8.043846334944299e-05,
149
+ "loss": 1.6542,
150
+ "step": 100
151
+ },
152
+ {
153
+ "epoch": 0.24475524475524477,
154
+ "grad_norm": 0.2525842272998614,
155
+ "learning_rate": 8.03753010014858e-05,
156
+ "loss": 1.5055,
157
+ "step": 105
158
+ },
159
+ {
160
+ "epoch": 0.2564102564102564,
161
+ "grad_norm": 0.2848401355775407,
162
+ "learning_rate": 8.030743885917666e-05,
163
+ "loss": 1.5441,
164
+ "step": 110
165
+ },
166
+ {
167
+ "epoch": 0.2680652680652681,
168
+ "grad_norm": 0.2578389420241452,
169
+ "learning_rate": 8.023488760452522e-05,
170
+ "loss": 1.5164,
171
+ "step": 115
172
+ },
173
+ {
174
+ "epoch": 0.27972027972027974,
175
+ "grad_norm": 0.384485780217046,
176
+ "learning_rate": 8.01576586576425e-05,
177
+ "loss": 1.4309,
178
+ "step": 120
179
+ },
180
+ {
181
+ "epoch": 0.2913752913752914,
182
+ "grad_norm": 0.3005538892717842,
183
+ "learning_rate": 8.007576417494336e-05,
184
+ "loss": 1.4464,
185
+ "step": 125
186
+ },
187
+ {
188
+ "epoch": 0.30303030303030304,
189
+ "grad_norm": 0.3038129052309793,
190
+ "learning_rate": 7.998921704723294e-05,
191
+ "loss": 1.308,
192
+ "step": 130
193
+ },
194
+ {
195
+ "epoch": 0.3146853146853147,
196
+ "grad_norm": 0.27857195778115285,
197
+ "learning_rate": 7.989803089767754e-05,
198
+ "loss": 1.3887,
199
+ "step": 135
200
+ },
201
+ {
202
+ "epoch": 0.32634032634032634,
203
+ "grad_norm": 0.2852295677864667,
204
+ "learning_rate": 7.980222007966029e-05,
205
+ "loss": 1.4992,
206
+ "step": 140
207
+ },
208
+ {
209
+ "epoch": 0.337995337995338,
210
+ "grad_norm": 0.2744064066208899,
211
+ "learning_rate": 7.970179967452175e-05,
212
+ "loss": 1.4618,
213
+ "step": 145
214
+ },
215
+ {
216
+ "epoch": 0.34965034965034963,
217
+ "grad_norm": 0.24802775085025972,
218
+ "learning_rate": 7.959678548918605e-05,
219
+ "loss": 1.3894,
220
+ "step": 150
221
+ },
222
+ {
223
+ "epoch": 0.3613053613053613,
224
+ "grad_norm": 0.25341971271489,
225
+ "learning_rate": 7.948719405367275e-05,
226
+ "loss": 1.402,
227
+ "step": 155
228
+ },
229
+ {
230
+ "epoch": 0.372960372960373,
231
+ "grad_norm": 0.24564392308719407,
232
+ "learning_rate": 7.937304261849485e-05,
233
+ "loss": 1.3474,
234
+ "step": 160
235
+ },
236
+ {
237
+ "epoch": 0.38461538461538464,
238
+ "grad_norm": 0.28202938683817624,
239
+ "learning_rate": 7.925434915194349e-05,
240
+ "loss": 1.4338,
241
+ "step": 165
242
+ },
243
+ {
244
+ "epoch": 0.3962703962703963,
245
+ "grad_norm": 0.310609971889877,
246
+ "learning_rate": 7.913113233725954e-05,
247
+ "loss": 1.4238,
248
+ "step": 170
249
+ },
250
+ {
251
+ "epoch": 0.40792540792540793,
252
+ "grad_norm": 0.27009263717875037,
253
+ "learning_rate": 7.90034115696928e-05,
254
+ "loss": 1.3496,
255
+ "step": 175
256
+ },
257
+ {
258
+ "epoch": 0.4195804195804196,
259
+ "grad_norm": 0.2710853328115736,
260
+ "learning_rate": 7.887120695344898e-05,
261
+ "loss": 1.4584,
262
+ "step": 180
263
+ },
264
+ {
265
+ "epoch": 0.43123543123543123,
266
+ "grad_norm": 0.25152522039701575,
267
+ "learning_rate": 7.873453929852514e-05,
268
+ "loss": 1.3774,
269
+ "step": 185
270
+ },
271
+ {
272
+ "epoch": 0.4428904428904429,
273
+ "grad_norm": 0.2835745821601218,
274
+ "learning_rate": 7.85934301174341e-05,
275
+ "loss": 1.4099,
276
+ "step": 190
277
+ },
278
+ {
279
+ "epoch": 0.45454545454545453,
280
+ "grad_norm": 1.0519805093542818,
281
+ "learning_rate": 7.844790162181818e-05,
282
+ "loss": 1.437,
283
+ "step": 195
284
+ },
285
+ {
286
+ "epoch": 0.4662004662004662,
287
+ "grad_norm": 0.8265825248892074,
288
+ "learning_rate": 7.829797671895288e-05,
289
+ "loss": 1.4522,
290
+ "step": 200
291
+ },
292
+ {
293
+ "epoch": 0.47785547785547783,
294
+ "grad_norm": 0.7862211345050619,
295
+ "learning_rate": 7.814367900814116e-05,
296
+ "loss": 1.4808,
297
+ "step": 205
298
+ },
299
+ {
300
+ "epoch": 0.48951048951048953,
301
+ "grad_norm": 2.729527753162334,
302
+ "learning_rate": 7.79850327769987e-05,
303
+ "loss": 1.3966,
304
+ "step": 210
305
+ },
306
+ {
307
+ "epoch": 0.5011655011655012,
308
+ "grad_norm": 0.5270917240760644,
309
+ "learning_rate": 7.78220629976309e-05,
310
+ "loss": 1.4515,
311
+ "step": 215
312
+ },
313
+ {
314
+ "epoch": 0.5128205128205128,
315
+ "grad_norm": 0.2370434474197243,
316
+ "learning_rate": 7.765479532270198e-05,
317
+ "loss": 1.354,
318
+ "step": 220
319
+ },
320
+ {
321
+ "epoch": 0.5244755244755245,
322
+ "grad_norm": 0.302576280537011,
323
+ "learning_rate": 7.748325608139717e-05,
324
+ "loss": 1.4122,
325
+ "step": 225
326
+ },
327
+ {
328
+ "epoch": 0.5361305361305362,
329
+ "grad_norm": 0.26006318976574305,
330
+ "learning_rate": 7.730747227527824e-05,
331
+ "loss": 1.4065,
332
+ "step": 230
333
+ },
334
+ {
335
+ "epoch": 0.5477855477855478,
336
+ "grad_norm": 0.25033459622615245,
337
+ "learning_rate": 7.712747157403322e-05,
338
+ "loss": 1.3791,
339
+ "step": 235
340
+ },
341
+ {
342
+ "epoch": 0.5594405594405595,
343
+ "grad_norm": 0.22820286614092533,
344
+ "learning_rate": 7.694328231112112e-05,
345
+ "loss": 1.339,
346
+ "step": 240
347
+ },
348
+ {
349
+ "epoch": 0.5710955710955711,
350
+ "grad_norm": 0.2808234577155991,
351
+ "learning_rate": 7.675493347931184e-05,
352
+ "loss": 1.391,
353
+ "step": 245
354
+ },
355
+ {
356
+ "epoch": 0.5827505827505828,
357
+ "grad_norm": 0.248396781368916,
358
+ "learning_rate": 7.656245472612264e-05,
359
+ "loss": 1.3796,
360
+ "step": 250
361
+ },
362
+ {
363
+ "epoch": 0.5944055944055944,
364
+ "grad_norm": 0.24239687758201922,
365
+ "learning_rate": 7.636587634915133e-05,
366
+ "loss": 1.2704,
367
+ "step": 255
368
+ },
369
+ {
370
+ "epoch": 0.6060606060606061,
371
+ "grad_norm": 0.2889579270489845,
372
+ "learning_rate": 7.616522929130724e-05,
373
+ "loss": 1.3738,
374
+ "step": 260
375
+ },
376
+ {
377
+ "epoch": 0.6177156177156177,
378
+ "grad_norm": 0.37773683176723527,
379
+ "learning_rate": 7.596054513594051e-05,
380
+ "loss": 1.2168,
381
+ "step": 265
382
+ },
383
+ {
384
+ "epoch": 0.6293706293706294,
385
+ "grad_norm": 0.2507614413849896,
386
+ "learning_rate": 7.575185610187072e-05,
387
+ "loss": 1.2799,
388
+ "step": 270
389
+ },
390
+ {
391
+ "epoch": 0.6410256410256411,
392
+ "grad_norm": 0.2519925650582622,
393
+ "learning_rate": 7.553919503831533e-05,
394
+ "loss": 1.3737,
395
+ "step": 275
396
+ },
397
+ {
398
+ "epoch": 0.6526806526806527,
399
+ "grad_norm": 0.25693488058335956,
400
+ "learning_rate": 7.532259541971902e-05,
401
+ "loss": 1.3132,
402
+ "step": 280
403
+ },
404
+ {
405
+ "epoch": 0.6643356643356644,
406
+ "grad_norm": 0.2654099769032578,
407
+ "learning_rate": 7.510209134048455e-05,
408
+ "loss": 1.336,
409
+ "step": 285
410
+ },
411
+ {
412
+ "epoch": 0.675990675990676,
413
+ "grad_norm": 0.2991450312535211,
414
+ "learning_rate": 7.4877717509606e-05,
415
+ "loss": 1.3136,
416
+ "step": 290
417
+ },
418
+ {
419
+ "epoch": 0.6876456876456877,
420
+ "grad_norm": 0.7936383565363224,
421
+ "learning_rate": 7.46495092452054e-05,
422
+ "loss": 1.3218,
423
+ "step": 295
424
+ },
425
+ {
426
+ "epoch": 0.6993006993006993,
427
+ "grad_norm": 0.2833344928086715,
428
+ "learning_rate": 7.441750246897328e-05,
429
+ "loss": 1.3775,
430
+ "step": 300
431
+ },
432
+ {
433
+ "epoch": 0.710955710955711,
434
+ "grad_norm": 0.23315264052796472,
435
+ "learning_rate": 7.418173370051446e-05,
436
+ "loss": 1.3401,
437
+ "step": 305
438
+ },
439
+ {
440
+ "epoch": 0.7226107226107226,
441
+ "grad_norm": 0.27055343448065056,
442
+ "learning_rate": 7.394224005159947e-05,
443
+ "loss": 1.3282,
444
+ "step": 310
445
+ },
446
+ {
447
+ "epoch": 0.7342657342657343,
448
+ "grad_norm": 0.2480849022059861,
449
+ "learning_rate": 7.369905922032295e-05,
450
+ "loss": 1.2888,
451
+ "step": 315
452
+ },
453
+ {
454
+ "epoch": 0.745920745920746,
455
+ "grad_norm": 0.31945412606809426,
456
+ "learning_rate": 7.345222948516969e-05,
457
+ "loss": 1.4228,
458
+ "step": 320
459
+ },
460
+ {
461
+ "epoch": 0.7575757575757576,
462
+ "grad_norm": 0.2576143196799571,
463
+ "learning_rate": 7.320178969898926e-05,
464
+ "loss": 1.3058,
465
+ "step": 325
466
+ },
467
+ {
468
+ "epoch": 0.7692307692307693,
469
+ "grad_norm": 0.43520117132833047,
470
+ "learning_rate": 7.294777928288031e-05,
471
+ "loss": 1.3131,
472
+ "step": 330
473
+ },
474
+ {
475
+ "epoch": 0.7808857808857809,
476
+ "grad_norm": 0.2882495350884511,
477
+ "learning_rate": 7.26902382199854e-05,
478
+ "loss": 1.32,
479
+ "step": 335
480
+ },
481
+ {
482
+ "epoch": 0.7925407925407926,
483
+ "grad_norm": 0.33796460872196393,
484
+ "learning_rate": 7.242920704919733e-05,
485
+ "loss": 1.3031,
486
+ "step": 340
487
+ },
488
+ {
489
+ "epoch": 0.8041958041958042,
490
+ "grad_norm": 0.2549144290343736,
491
+ "learning_rate": 7.216472685877808e-05,
492
+ "loss": 1.2656,
493
+ "step": 345
494
+ },
495
+ {
496
+ "epoch": 0.8158508158508159,
497
+ "grad_norm": 0.6420737440392777,
498
+ "learning_rate": 7.189683927989109e-05,
499
+ "loss": 1.3621,
500
+ "step": 350
501
+ },
502
+ {
503
+ "epoch": 0.8275058275058275,
504
+ "grad_norm": 0.25149854473667893,
505
+ "learning_rate": 7.162558648004833e-05,
506
+ "loss": 1.3055,
507
+ "step": 355
508
+ },
509
+ {
510
+ "epoch": 0.8391608391608392,
511
+ "grad_norm": 0.8756690609514122,
512
+ "learning_rate": 7.13510111564727e-05,
513
+ "loss": 1.306,
514
+ "step": 360
515
+ },
516
+ {
517
+ "epoch": 0.8508158508158508,
518
+ "grad_norm": 0.27473178820064537,
519
+ "learning_rate": 7.107315652937733e-05,
520
+ "loss": 1.3125,
521
+ "step": 365
522
+ },
523
+ {
524
+ "epoch": 0.8624708624708625,
525
+ "grad_norm": 5.526242806524436,
526
+ "learning_rate": 7.079206633516216e-05,
527
+ "loss": 1.2443,
528
+ "step": 370
529
+ },
530
+ {
531
+ "epoch": 0.8741258741258742,
532
+ "grad_norm": 0.2859887823856341,
533
+ "learning_rate": 7.050778481952977e-05,
534
+ "loss": 1.3051,
535
+ "step": 375
536
+ },
537
+ {
538
+ "epoch": 0.8857808857808858,
539
+ "grad_norm": 0.26065360686340344,
540
+ "learning_rate": 7.022035673052052e-05,
541
+ "loss": 1.2533,
542
+ "step": 380
543
+ },
544
+ {
545
+ "epoch": 0.8974358974358975,
546
+ "grad_norm": 0.28515419529118324,
547
+ "learning_rate": 6.992982731146909e-05,
548
+ "loss": 1.292,
549
+ "step": 385
550
+ },
551
+ {
552
+ "epoch": 0.9090909090909091,
553
+ "grad_norm": 0.2521847950964824,
554
+ "learning_rate": 6.963624229388268e-05,
555
+ "loss": 1.3149,
556
+ "step": 390
557
+ },
558
+ {
559
+ "epoch": 0.9207459207459208,
560
+ "grad_norm": 0.24378682997123743,
561
+ "learning_rate": 6.933964789024263e-05,
562
+ "loss": 1.299,
563
+ "step": 395
564
+ },
565
+ {
566
+ "epoch": 0.9324009324009324,
567
+ "grad_norm": 0.22312967942400147,
568
+ "learning_rate": 6.904009078673016e-05,
569
+ "loss": 1.2422,
570
+ "step": 400
571
+ },
572
+ {
573
+ "epoch": 0.9440559440559441,
574
+ "grad_norm": 0.22503476475625694,
575
+ "learning_rate": 6.873761813587769e-05,
576
+ "loss": 1.2913,
577
+ "step": 405
578
+ },
579
+ {
580
+ "epoch": 0.9557109557109557,
581
+ "grad_norm": 0.22697946460375637,
582
+ "learning_rate": 6.843227754914657e-05,
583
+ "loss": 1.29,
584
+ "step": 410
585
+ },
586
+ {
587
+ "epoch": 0.9673659673659674,
588
+ "grad_norm": 0.3144384632248903,
589
+ "learning_rate": 6.812411708943284e-05,
590
+ "loss": 1.2395,
591
+ "step": 415
592
+ },
593
+ {
594
+ "epoch": 0.9790209790209791,
595
+ "grad_norm": 0.24364089502734793,
596
+ "learning_rate": 6.781318526350156e-05,
597
+ "loss": 1.4002,
598
+ "step": 420
599
+ },
600
+ {
601
+ "epoch": 0.9906759906759907,
602
+ "grad_norm": 0.23043000137266378,
603
+ "learning_rate": 6.749953101435168e-05,
604
+ "loss": 1.2886,
605
+ "step": 425
606
+ },
607
+ {
608
+ "epoch": 0.9976689976689976,
609
+ "eval_loss": 1.346985936164856,
610
+ "eval_runtime": 41.4179,
611
+ "eval_samples_per_second": 1.69,
612
+ "eval_steps_per_second": 0.217,
613
+ "step": 428
614
+ },
615
+ {
616
+ "epoch": 1.0023310023310024,
617
+ "grad_norm": 0.6370362893316296,
618
+ "learning_rate": 6.718320371351193e-05,
619
+ "loss": 1.2846,
620
+ "step": 430
621
+ },
622
+ {
623
+ "epoch": 1.013986013986014,
624
+ "grad_norm": 0.26814660795194867,
625
+ "learning_rate": 6.686425315326941e-05,
626
+ "loss": 1.0865,
627
+ "step": 435
628
+ },
629
+ {
630
+ "epoch": 1.0256410256410255,
631
+ "grad_norm": 0.23807462749178174,
632
+ "learning_rate": 6.654272953883189e-05,
633
+ "loss": 1.1612,
634
+ "step": 440
635
+ },
636
+ {
637
+ "epoch": 1.0372960372960374,
638
+ "grad_norm": 0.23960120741081306,
639
+ "learning_rate": 6.621868348042517e-05,
640
+ "loss": 1.1393,
641
+ "step": 445
642
+ },
643
+ {
644
+ "epoch": 1.048951048951049,
645
+ "grad_norm": 0.2601814951485897,
646
+ "learning_rate": 6.58921659853266e-05,
647
+ "loss": 1.2539,
648
+ "step": 450
649
+ },
650
+ {
651
+ "epoch": 1.0606060606060606,
652
+ "grad_norm": 0.2489367328385621,
653
+ "learning_rate": 6.55632284498362e-05,
654
+ "loss": 1.1934,
655
+ "step": 455
656
+ },
657
+ {
658
+ "epoch": 1.0722610722610724,
659
+ "grad_norm": 0.26068816228316616,
660
+ "learning_rate": 6.523192265118652e-05,
661
+ "loss": 1.252,
662
+ "step": 460
663
+ },
664
+ {
665
+ "epoch": 1.083916083916084,
666
+ "grad_norm": 0.2681555770705724,
667
+ "learning_rate": 6.489830073939237e-05,
668
+ "loss": 1.2231,
669
+ "step": 465
670
+ },
671
+ {
672
+ "epoch": 1.0955710955710956,
673
+ "grad_norm": 0.24692924998707827,
674
+ "learning_rate": 6.456241522904223e-05,
675
+ "loss": 1.1952,
676
+ "step": 470
677
+ },
678
+ {
679
+ "epoch": 1.1072261072261071,
680
+ "grad_norm": 0.24530619885017255,
681
+ "learning_rate": 6.422431899103189e-05,
682
+ "loss": 1.1665,
683
+ "step": 475
684
+ },
685
+ {
686
+ "epoch": 1.118881118881119,
687
+ "grad_norm": 0.2677189175766508,
688
+ "learning_rate": 6.388406524424222e-05,
689
+ "loss": 1.176,
690
+ "step": 480
691
+ },
692
+ {
693
+ "epoch": 1.1305361305361306,
694
+ "grad_norm": 0.2411887554782912,
695
+ "learning_rate": 6.35417075471622e-05,
696
+ "loss": 1.1704,
697
+ "step": 485
698
+ },
699
+ {
700
+ "epoch": 1.1421911421911422,
701
+ "grad_norm": 0.2541256840409212,
702
+ "learning_rate": 6.319729978945832e-05,
703
+ "loss": 1.1782,
704
+ "step": 490
705
+ },
706
+ {
707
+ "epoch": 1.1538461538461537,
708
+ "grad_norm": 0.24850101976269176,
709
+ "learning_rate": 6.285089618349196e-05,
710
+ "loss": 1.1847,
711
+ "step": 495
712
+ },
713
+ {
714
+ "epoch": 1.1655011655011656,
715
+ "grad_norm": 0.2672134029476264,
716
+ "learning_rate": 6.250255125578597e-05,
717
+ "loss": 1.0407,
718
+ "step": 500
719
+ },
720
+ {
721
+ "epoch": 1.1655011655011656,
722
+ "eval_loss": 1.335543155670166,
723
+ "eval_runtime": 41.117,
724
+ "eval_samples_per_second": 1.702,
725
+ "eval_steps_per_second": 0.219,
726
+ "step": 500
727
+ },
728
+ {
729
+ "epoch": 1.1771561771561772,
730
+ "grad_norm": 0.24056303633515866,
731
+ "learning_rate": 6.21523198384418e-05,
732
+ "loss": 1.223,
733
+ "step": 505
734
+ },
735
+ {
736
+ "epoch": 1.1888111888111887,
737
+ "grad_norm": 0.25656987276961235,
738
+ "learning_rate": 6.18002570605085e-05,
739
+ "loss": 1.1589,
740
+ "step": 510
741
+ },
742
+ {
743
+ "epoch": 1.2004662004662006,
744
+ "grad_norm": 0.25884269499583334,
745
+ "learning_rate": 6.144641833930498e-05,
746
+ "loss": 1.1185,
747
+ "step": 515
748
+ },
749
+ {
750
+ "epoch": 1.2121212121212122,
751
+ "grad_norm": 0.24120488400409848,
752
+ "learning_rate": 6.109085937169695e-05,
753
+ "loss": 1.2347,
754
+ "step": 520
755
+ },
756
+ {
757
+ "epoch": 1.2237762237762237,
758
+ "grad_norm": 0.24337953823169015,
759
+ "learning_rate": 6.0733636125329776e-05,
760
+ "loss": 1.0777,
761
+ "step": 525
762
+ },
763
+ {
764
+ "epoch": 1.2354312354312353,
765
+ "grad_norm": 0.2553344373947113,
766
+ "learning_rate": 6.0374804829818786e-05,
767
+ "loss": 1.1297,
768
+ "step": 530
769
+ },
770
+ {
771
+ "epoch": 1.2470862470862472,
772
+ "grad_norm": 0.26618655203985797,
773
+ "learning_rate": 6.001442196789827e-05,
774
+ "loss": 1.1129,
775
+ "step": 535
776
+ },
777
+ {
778
+ "epoch": 1.2587412587412588,
779
+ "grad_norm": 0.2631162852747018,
780
+ "learning_rate": 5.965254426653072e-05,
781
+ "loss": 1.2239,
782
+ "step": 540
783
+ },
784
+ {
785
+ "epoch": 1.2703962703962703,
786
+ "grad_norm": 0.23274413800511448,
787
+ "learning_rate": 5.928922868797752e-05,
788
+ "loss": 1.103,
789
+ "step": 545
790
+ },
791
+ {
792
+ "epoch": 1.282051282051282,
793
+ "grad_norm": 0.23157161304838858,
794
+ "learning_rate": 5.892453242083273e-05,
795
+ "loss": 1.0679,
796
+ "step": 550
797
+ },
798
+ {
799
+ "epoch": 1.2937062937062938,
800
+ "grad_norm": 0.28740045332560504,
801
+ "learning_rate": 5.855851287102113e-05,
802
+ "loss": 1.1891,
803
+ "step": 555
804
+ },
805
+ {
806
+ "epoch": 1.3053613053613053,
807
+ "grad_norm": 0.2970846582151576,
808
+ "learning_rate": 5.81912276527621e-05,
809
+ "loss": 1.1354,
810
+ "step": 560
811
+ },
812
+ {
813
+ "epoch": 1.317016317016317,
814
+ "grad_norm": 0.2630829061530002,
815
+ "learning_rate": 5.7822734579500705e-05,
816
+ "loss": 1.1793,
817
+ "step": 565
818
+ },
819
+ {
820
+ "epoch": 1.3286713286713288,
821
+ "grad_norm": 0.24952577498784723,
822
+ "learning_rate": 5.745309165480747e-05,
823
+ "loss": 1.0412,
824
+ "step": 570
825
+ },
826
+ {
827
+ "epoch": 1.3403263403263403,
828
+ "grad_norm": 0.29261484653650605,
829
+ "learning_rate": 5.7082357063248116e-05,
830
+ "loss": 1.1266,
831
+ "step": 575
832
+ },
833
+ {
834
+ "epoch": 1.351981351981352,
835
+ "grad_norm": 0.27423549595827834,
836
+ "learning_rate": 5.671058916122493e-05,
837
+ "loss": 1.1526,
838
+ "step": 580
839
+ },
840
+ {
841
+ "epoch": 1.3636363636363638,
842
+ "grad_norm": 0.26193784576015794,
843
+ "learning_rate": 5.6337846467790995e-05,
844
+ "loss": 1.1818,
845
+ "step": 585
846
+ },
847
+ {
848
+ "epoch": 1.3752913752913754,
849
+ "grad_norm": 0.2536711363621732,
850
+ "learning_rate": 5.596418765543887e-05,
851
+ "loss": 1.1099,
852
+ "step": 590
853
+ },
854
+ {
855
+ "epoch": 1.386946386946387,
856
+ "grad_norm": 0.25809295106016567,
857
+ "learning_rate": 5.55896715408651e-05,
858
+ "loss": 1.1281,
859
+ "step": 595
860
+ },
861
+ {
862
+ "epoch": 1.3986013986013985,
863
+ "grad_norm": 0.2964280224538696,
864
+ "learning_rate": 5.521435707571199e-05,
865
+ "loss": 1.1209,
866
+ "step": 600
867
+ },
868
+ {
869
+ "epoch": 1.4102564102564101,
870
+ "grad_norm": 0.2535619637821886,
871
+ "learning_rate": 5.483830333728829e-05,
872
+ "loss": 1.0736,
873
+ "step": 605
874
+ },
875
+ {
876
+ "epoch": 1.421911421911422,
877
+ "grad_norm": 0.2834714269145168,
878
+ "learning_rate": 5.4461569519269803e-05,
879
+ "loss": 1.0904,
880
+ "step": 610
881
+ },
882
+ {
883
+ "epoch": 1.4335664335664335,
884
+ "grad_norm": 0.26457948671956855,
885
+ "learning_rate": 5.4084214922382015e-05,
886
+ "loss": 1.1718,
887
+ "step": 615
888
+ },
889
+ {
890
+ "epoch": 1.4452214452214451,
891
+ "grad_norm": 0.30016622504388313,
892
+ "learning_rate": 5.370629894506561e-05,
893
+ "loss": 1.1222,
894
+ "step": 620
895
+ },
896
+ {
897
+ "epoch": 1.456876456876457,
898
+ "grad_norm": 0.24560811509210745,
899
+ "learning_rate": 5.332788107412684e-05,
900
+ "loss": 1.1179,
901
+ "step": 625
902
+ },
903
+ {
904
+ "epoch": 1.4685314685314685,
905
+ "grad_norm": 0.27129656920581763,
906
+ "learning_rate": 5.294902087537369e-05,
907
+ "loss": 1.1379,
908
+ "step": 630
909
+ },
910
+ {
911
+ "epoch": 1.4801864801864801,
912
+ "grad_norm": 0.26155557293622045,
913
+ "learning_rate": 5.256977798423988e-05,
914
+ "loss": 1.1354,
915
+ "step": 635
916
+ },
917
+ {
918
+ "epoch": 1.491841491841492,
919
+ "grad_norm": 0.2542515790861205,
920
+ "learning_rate": 5.2190212096397825e-05,
921
+ "loss": 1.0926,
922
+ "step": 640
923
+ },
924
+ {
925
+ "epoch": 1.5034965034965035,
926
+ "grad_norm": 0.2846310062143532,
927
+ "learning_rate": 5.181038295836196e-05,
928
+ "loss": 1.206,
929
+ "step": 645
930
+ },
931
+ {
932
+ "epoch": 1.5151515151515151,
933
+ "grad_norm": 0.2578892076658671,
934
+ "learning_rate": 5.143035035808435e-05,
935
+ "loss": 1.1348,
936
+ "step": 650
937
+ },
938
+ {
939
+ "epoch": 1.526806526806527,
940
+ "grad_norm": 0.2677065667604314,
941
+ "learning_rate": 5.1050174115543476e-05,
942
+ "loss": 1.1376,
943
+ "step": 655
944
+ },
945
+ {
946
+ "epoch": 1.5384615384615383,
947
+ "grad_norm": 0.2623622010580359,
948
+ "learning_rate": 5.066991407332825e-05,
949
+ "loss": 1.147,
950
+ "step": 660
951
+ },
952
+ {
953
+ "epoch": 1.5501165501165501,
954
+ "grad_norm": 0.2924192984321144,
955
+ "learning_rate": 5.028963008721822e-05,
956
+ "loss": 1.2343,
957
+ "step": 665
958
+ },
959
+ {
960
+ "epoch": 1.5617715617715617,
961
+ "grad_norm": 0.25879469972966473,
962
+ "learning_rate": 4.990938201676194e-05,
963
+ "loss": 1.1271,
964
+ "step": 670
965
+ },
966
+ {
967
+ "epoch": 1.5734265734265733,
968
+ "grad_norm": 0.2738138873868371,
969
+ "learning_rate": 4.952922971585451e-05,
970
+ "loss": 1.0558,
971
+ "step": 675
972
+ },
973
+ {
974
+ "epoch": 1.5850815850815851,
975
+ "grad_norm": 0.24373153596626246,
976
+ "learning_rate": 4.914923302331625e-05,
977
+ "loss": 1.1583,
978
+ "step": 680
979
+ },
980
+ {
981
+ "epoch": 1.5967365967365967,
982
+ "grad_norm": 0.26700970389535894,
983
+ "learning_rate": 4.87694517534735e-05,
984
+ "loss": 1.0228,
985
+ "step": 685
986
+ },
987
+ {
988
+ "epoch": 1.6083916083916083,
989
+ "grad_norm": 0.29201876514809744,
990
+ "learning_rate": 4.838994568674351e-05,
991
+ "loss": 1.1897,
992
+ "step": 690
993
+ },
994
+ {
995
+ "epoch": 1.6200466200466201,
996
+ "grad_norm": 0.2731368722942658,
997
+ "learning_rate": 4.801077456022443e-05,
998
+ "loss": 1.2347,
999
+ "step": 695
1000
+ },
1001
+ {
1002
+ "epoch": 1.6317016317016317,
1003
+ "grad_norm": 0.24941385151182885,
1004
+ "learning_rate": 4.763199805829236e-05,
1005
+ "loss": 1.0522,
1006
+ "step": 700
1007
+ },
1008
+ {
1009
+ "epoch": 1.6433566433566433,
1010
+ "grad_norm": 0.2601913077602386,
1011
+ "learning_rate": 4.7253675803206544e-05,
1012
+ "loss": 1.1047,
1013
+ "step": 705
1014
+ },
1015
+ {
1016
+ "epoch": 1.6550116550116551,
1017
+ "grad_norm": 0.2627466378538171,
1018
+ "learning_rate": 4.687586734572431e-05,
1019
+ "loss": 1.2039,
1020
+ "step": 710
1021
+ },
1022
+ {
1023
+ "epoch": 1.6666666666666665,
1024
+ "grad_norm": 0.33292973388136243,
1025
+ "learning_rate": 4.649863215572747e-05,
1026
+ "loss": 1.0949,
1027
+ "step": 715
1028
+ },
1029
+ {
1030
+ "epoch": 1.6783216783216783,
1031
+ "grad_norm": 0.28930444872767674,
1032
+ "learning_rate": 4.612202961286117e-05,
1033
+ "loss": 1.1411,
1034
+ "step": 720
1035
+ },
1036
+ {
1037
+ "epoch": 1.68997668997669,
1038
+ "grad_norm": 0.2811673269560653,
1039
+ "learning_rate": 4.574611899718721e-05,
1040
+ "loss": 1.1188,
1041
+ "step": 725
1042
+ },
1043
+ {
1044
+ "epoch": 1.7016317016317015,
1045
+ "grad_norm": 0.2624778144533447,
1046
+ "learning_rate": 4.537095947985282e-05,
1047
+ "loss": 1.2099,
1048
+ "step": 730
1049
+ },
1050
+ {
1051
+ "epoch": 1.7132867132867133,
1052
+ "grad_norm": 0.31909240386960064,
1053
+ "learning_rate": 4.499661011377677e-05,
1054
+ "loss": 1.1953,
1055
+ "step": 735
1056
+ },
1057
+ {
1058
+ "epoch": 1.724941724941725,
1059
+ "grad_norm": 0.45177444374511333,
1060
+ "learning_rate": 4.46231298243539e-05,
1061
+ "loss": 1.1496,
1062
+ "step": 740
1063
+ },
1064
+ {
1065
+ "epoch": 1.7365967365967365,
1066
+ "grad_norm": 0.3304135322652554,
1067
+ "learning_rate": 4.425057740017993e-05,
1068
+ "loss": 1.1407,
1069
+ "step": 745
1070
+ },
1071
+ {
1072
+ "epoch": 1.7482517482517483,
1073
+ "grad_norm": 0.26814860174828314,
1074
+ "learning_rate": 4.38790114837976e-05,
1075
+ "loss": 1.0907,
1076
+ "step": 750
1077
+ },
1078
+ {
1079
+ "epoch": 1.75990675990676,
1080
+ "grad_norm": 0.29715139148195335,
1081
+ "learning_rate": 4.350849056246595e-05,
1082
+ "loss": 1.1766,
1083
+ "step": 755
1084
+ },
1085
+ {
1086
+ "epoch": 1.7715617715617715,
1087
+ "grad_norm": 0.274851580699654,
1088
+ "learning_rate": 4.313907295895397e-05,
1089
+ "loss": 1.1497,
1090
+ "step": 760
1091
+ },
1092
+ {
1093
+ "epoch": 1.7832167832167833,
1094
+ "grad_norm": 0.30500141557968397,
1095
+ "learning_rate": 4.277081682236013e-05,
1096
+ "loss": 1.0404,
1097
+ "step": 765
1098
+ },
1099
+ {
1100
+ "epoch": 1.7948717948717947,
1101
+ "grad_norm": 2.9176458727968746,
1102
+ "learning_rate": 4.240378011895935e-05,
1103
+ "loss": 1.0777,
1104
+ "step": 770
1105
+ },
1106
+ {
1107
+ "epoch": 1.8065268065268065,
1108
+ "grad_norm": 0.32004127534889776,
1109
+ "learning_rate": 4.2038020623078596e-05,
1110
+ "loss": 1.1521,
1111
+ "step": 775
1112
+ },
1113
+ {
1114
+ "epoch": 1.8181818181818183,
1115
+ "grad_norm": 0.38996610677191895,
1116
+ "learning_rate": 4.1673595908002826e-05,
1117
+ "loss": 1.0999,
1118
+ "step": 780
1119
+ },
1120
+ {
1121
+ "epoch": 1.8298368298368297,
1122
+ "grad_norm": 0.39155093719025963,
1123
+ "learning_rate": 4.131056333691247e-05,
1124
+ "loss": 1.1836,
1125
+ "step": 785
1126
+ },
1127
+ {
1128
+ "epoch": 1.8414918414918415,
1129
+ "grad_norm": 0.2765149318590016,
1130
+ "learning_rate": 4.094898005385408e-05,
1131
+ "loss": 1.1018,
1132
+ "step": 790
1133
+ },
1134
+ {
1135
+ "epoch": 1.8531468531468531,
1136
+ "grad_norm": 0.22839762225047938,
1137
+ "learning_rate": 4.058890297474543e-05,
1138
+ "loss": 1.1704,
1139
+ "step": 795
1140
+ },
1141
+ {
1142
+ "epoch": 1.8648018648018647,
1143
+ "grad_norm": 0.269742896374976,
1144
+ "learning_rate": 4.023038877841649e-05,
1145
+ "loss": 1.0703,
1146
+ "step": 800
1147
+ },
1148
+ {
1149
+ "epoch": 1.8764568764568765,
1150
+ "grad_norm": 0.29602473720606215,
1151
+ "learning_rate": 3.987349389768777e-05,
1152
+ "loss": 1.1029,
1153
+ "step": 805
1154
+ },
1155
+ {
1156
+ "epoch": 1.8881118881118881,
1157
+ "grad_norm": 0.2609207540513949,
1158
+ "learning_rate": 3.951827451048737e-05,
1159
+ "loss": 1.2367,
1160
+ "step": 810
1161
+ },
1162
+ {
1163
+ "epoch": 1.8997668997668997,
1164
+ "grad_norm": 0.2508364860523673,
1165
+ "learning_rate": 3.916478653100816e-05,
1166
+ "loss": 1.0849,
1167
+ "step": 815
1168
+ },
1169
+ {
1170
+ "epoch": 1.9114219114219115,
1171
+ "grad_norm": 1.2856984958855535,
1172
+ "learning_rate": 3.881308560090648e-05,
1173
+ "loss": 1.1273,
1174
+ "step": 820
1175
+ },
1176
+ {
1177
+ "epoch": 1.9230769230769231,
1178
+ "grad_norm": 0.24270883363297913,
1179
+ "learning_rate": 3.846322708054368e-05,
1180
+ "loss": 1.1128,
1181
+ "step": 825
1182
+ },
1183
+ {
1184
+ "epoch": 1.9347319347319347,
1185
+ "grad_norm": 0.26881059124314843,
1186
+ "learning_rate": 3.811526604027204e-05,
1187
+ "loss": 1.2133,
1188
+ "step": 830
1189
+ },
1190
+ {
1191
+ "epoch": 1.9463869463869465,
1192
+ "grad_norm": 0.2878909720257614,
1193
+ "learning_rate": 3.7769257251766225e-05,
1194
+ "loss": 1.1629,
1195
+ "step": 835
1196
+ },
1197
+ {
1198
+ "epoch": 1.958041958041958,
1199
+ "grad_norm": 0.31812523517669944,
1200
+ "learning_rate": 3.742525517940187e-05,
1201
+ "loss": 1.149,
1202
+ "step": 840
1203
+ },
1204
+ {
1205
+ "epoch": 1.9696969696969697,
1206
+ "grad_norm": 0.27576941685401857,
1207
+ "learning_rate": 3.708331397168247e-05,
1208
+ "loss": 1.1484,
1209
+ "step": 845
1210
+ },
1211
+ {
1212
+ "epoch": 1.9813519813519813,
1213
+ "grad_norm": 0.27263251333241223,
1214
+ "learning_rate": 3.674348745271595e-05,
1215
+ "loss": 1.1931,
1216
+ "step": 850
1217
+ },
1218
+ {
1219
+ "epoch": 1.993006993006993,
1220
+ "grad_norm": 0.263716889490106,
1221
+ "learning_rate": 3.6405829113742405e-05,
1222
+ "loss": 1.1308,
1223
+ "step": 855
1224
+ },
1225
+ {
1226
+ "epoch": 1.9953379953379953,
1227
+ "eval_loss": 1.2667760848999023,
1228
+ "eval_runtime": 41.1775,
1229
+ "eval_samples_per_second": 1.7,
1230
+ "eval_steps_per_second": 0.219,
1231
+ "step": 856
1232
+ }
1233
+ ],
1234
+ "logging_steps": 5,
1235
+ "max_steps": 1287,
1236
+ "num_input_tokens_seen": 0,
1237
+ "num_train_epochs": 3,
1238
+ "save_steps": 500,
1239
+ "stateful_callbacks": {
1240
+ "TrainerControl": {
1241
+ "args": {
1242
+ "should_epoch_stop": false,
1243
+ "should_evaluate": false,
1244
+ "should_log": false,
1245
+ "should_save": true,
1246
+ "should_training_stop": false
1247
+ },
1248
+ "attributes": {}
1249
+ }
1250
+ },
1251
+ "total_flos": 887872819298304.0,
1252
+ "train_batch_size": 8,
1253
+ "trial_name": null,
1254
+ "trial_params": null
1255
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a800d03b526d467e2fcadee0f29680d19088aff8322ac8a7f79b8cca003b2c5
3
+ size 7480