Frinkles commited on
Commit
4947329
1 Parent(s): 72d3db5

initial_commit

Browse files
README.md CHANGED
@@ -1,3 +1,202 @@
1
- ---
2
- license: mit
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: microsoft/Phi-3-mini-4k-instruct
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 0.11.1
adapter_config.json CHANGED
@@ -20,10 +20,10 @@
20
  "rank_pattern": {},
21
  "revision": null,
22
  "target_modules": [
23
- "qkv_proj",
24
- "gate_up_proj",
25
  "down_proj",
26
- "o_proj"
 
27
  ],
28
  "task_type": "CAUSAL_LM",
29
  "use_dora": false,
 
20
  "rank_pattern": {},
21
  "revision": null,
22
  "target_modules": [
23
+ "o_proj",
 
24
  "down_proj",
25
+ "gate_up_proj",
26
+ "qkv_proj"
27
  ],
28
  "task_type": "CAUSAL_LM",
29
  "use_dora": false,
all_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
  "epoch": 1.0,
3
- "total_flos": 8.07158446678868e+17,
4
- "train_loss": 0.007153803548112083,
5
- "train_runtime": 33886.5214,
6
- "train_samples_per_second": 0.517,
7
- "train_steps_per_second": 0.129
8
  }
 
1
  {
2
  "epoch": 1.0,
3
+ "total_flos": 3.1269503354535936e+16,
4
+ "train_loss": 0.19359449498793657,
5
+ "train_runtime": 1514.0603,
6
+ "train_samples_per_second": 0.448,
7
+ "train_steps_per_second": 0.112
8
  }
train_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
  "epoch": 1.0,
3
- "total_flos": 8.07158446678868e+17,
4
- "train_loss": 0.007153803548112083,
5
- "train_runtime": 33886.5214,
6
- "train_samples_per_second": 0.517,
7
- "train_steps_per_second": 0.129
8
  }
 
1
  {
2
  "epoch": 1.0,
3
+ "total_flos": 3.1269503354535936e+16,
4
+ "train_loss": 0.19359449498793657,
5
+ "train_runtime": 1514.0603,
6
+ "train_samples_per_second": 0.448,
7
+ "train_steps_per_second": 0.112
8
  }
trainer_state.json CHANGED
@@ -3,632 +3,44 @@
3
  "best_model_checkpoint": null,
4
  "epoch": 1.0,
5
  "eval_steps": 500,
6
- "global_step": 4382,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
- "epoch": 0.011410314924691922,
13
  "grad_norm": NaN,
14
- "learning_rate": 2.850627137970354e-07,
15
- "loss": 0.627,
16
  "step": 50
17
  },
18
  {
19
- "epoch": 0.022820629849383843,
20
  "grad_norm": NaN,
21
- "learning_rate": 5.701254275940708e-07,
22
  "loss": 0.0,
23
  "step": 100
24
  },
25
  {
26
- "epoch": 0.03423094477407576,
27
  "grad_norm": NaN,
28
- "learning_rate": 8.551881413911062e-07,
29
  "loss": 0.0,
30
  "step": 150
31
  },
32
- {
33
- "epoch": 0.045641259698767686,
34
- "grad_norm": NaN,
35
- "learning_rate": 1.1402508551881415e-06,
36
- "loss": 0.0,
37
- "step": 200
38
- },
39
- {
40
- "epoch": 0.057051574623459604,
41
- "grad_norm": NaN,
42
- "learning_rate": 1.4253135689851768e-06,
43
- "loss": 0.0,
44
- "step": 250
45
- },
46
- {
47
- "epoch": 0.06846188954815152,
48
- "grad_norm": NaN,
49
- "learning_rate": 1.7103762827822124e-06,
50
- "loss": 0.0,
51
- "step": 300
52
- },
53
- {
54
- "epoch": 0.07987220447284345,
55
- "grad_norm": NaN,
56
- "learning_rate": 1.9954389965792477e-06,
57
- "loss": 0.0,
58
- "step": 350
59
- },
60
- {
61
- "epoch": 0.09128251939753537,
62
- "grad_norm": NaN,
63
- "learning_rate": 2.280501710376283e-06,
64
- "loss": 0.0,
65
- "step": 400
66
- },
67
- {
68
- "epoch": 0.1026928343222273,
69
- "grad_norm": NaN,
70
- "learning_rate": 2.5655644241733184e-06,
71
- "loss": 0.0,
72
- "step": 450
73
- },
74
- {
75
- "epoch": 0.11410314924691921,
76
- "grad_norm": NaN,
77
- "learning_rate": 2.8506271379703537e-06,
78
- "loss": 0.0,
79
- "step": 500
80
- },
81
- {
82
- "epoch": 0.12551346417161113,
83
- "grad_norm": NaN,
84
- "learning_rate": 3.135689851767389e-06,
85
- "loss": 0.0,
86
- "step": 550
87
- },
88
- {
89
- "epoch": 0.13692377909630304,
90
- "grad_norm": NaN,
91
- "learning_rate": 3.4207525655644248e-06,
92
- "loss": 0.0,
93
- "step": 600
94
- },
95
- {
96
- "epoch": 0.14833409402099498,
97
- "grad_norm": NaN,
98
- "learning_rate": 3.70581527936146e-06,
99
- "loss": 0.0,
100
- "step": 650
101
- },
102
- {
103
- "epoch": 0.1597444089456869,
104
- "grad_norm": NaN,
105
- "learning_rate": 3.990877993158495e-06,
106
- "loss": 0.0,
107
- "step": 700
108
- },
109
- {
110
- "epoch": 0.17115472387037883,
111
- "grad_norm": NaN,
112
- "learning_rate": 4.27594070695553e-06,
113
- "loss": 0.0,
114
- "step": 750
115
- },
116
- {
117
- "epoch": 0.18256503879507074,
118
- "grad_norm": NaN,
119
- "learning_rate": 4.561003420752566e-06,
120
- "loss": 0.0,
121
- "step": 800
122
- },
123
- {
124
- "epoch": 0.19397535371976266,
125
- "grad_norm": NaN,
126
- "learning_rate": 4.846066134549601e-06,
127
- "loss": 0.0,
128
- "step": 850
129
- },
130
- {
131
- "epoch": 0.2053856686444546,
132
- "grad_norm": NaN,
133
- "learning_rate": 4.9994687805047495e-06,
134
- "loss": 0.0,
135
- "step": 900
136
- },
137
- {
138
- "epoch": 0.2167959835691465,
139
- "grad_norm": NaN,
140
- "learning_rate": 4.994650360888966e-06,
141
- "loss": 0.0,
142
- "step": 950
143
- },
144
- {
145
- "epoch": 0.22820629849383842,
146
- "grad_norm": NaN,
147
- "learning_rate": 4.984822368325914e-06,
148
- "loss": 0.0,
149
- "step": 1000
150
- },
151
- {
152
- "epoch": 0.23961661341853036,
153
- "grad_norm": NaN,
154
- "learning_rate": 4.970004538665729e-06,
155
- "loss": 0.0,
156
- "step": 1050
157
- },
158
- {
159
- "epoch": 0.25102692834322227,
160
- "grad_norm": NaN,
161
- "learning_rate": 4.950226627981557e-06,
162
- "loss": 0.0,
163
- "step": 1100
164
- },
165
- {
166
- "epoch": 0.2624372432679142,
167
- "grad_norm": NaN,
168
- "learning_rate": 4.925528352815589e-06,
169
- "loss": 0.0,
170
- "step": 1150
171
- },
172
- {
173
- "epoch": 0.2738475581926061,
174
- "grad_norm": NaN,
175
- "learning_rate": 4.895959310423238e-06,
176
- "loss": 0.0,
177
- "step": 1200
178
- },
179
- {
180
- "epoch": 0.28525787311729806,
181
- "grad_norm": NaN,
182
- "learning_rate": 4.861578879175587e-06,
183
- "loss": 0.0,
184
- "step": 1250
185
- },
186
- {
187
- "epoch": 0.29666818804198997,
188
- "grad_norm": NaN,
189
- "learning_rate": 4.822456099320115e-06,
190
- "loss": 0.0,
191
- "step": 1300
192
- },
193
- {
194
- "epoch": 0.3080785029666819,
195
- "grad_norm": NaN,
196
- "learning_rate": 4.778669534339168e-06,
197
- "loss": 0.0,
198
- "step": 1350
199
- },
200
- {
201
- "epoch": 0.3194888178913738,
202
- "grad_norm": NaN,
203
- "learning_rate": 4.730307113184564e-06,
204
- "loss": 0.0,
205
- "step": 1400
206
- },
207
- {
208
- "epoch": 0.3308991328160657,
209
- "grad_norm": NaN,
210
- "learning_rate": 4.67746595370515e-06,
211
- "loss": 0.0,
212
- "step": 1450
213
- },
214
- {
215
- "epoch": 0.34230944774075767,
216
- "grad_norm": NaN,
217
- "learning_rate": 4.620252167621905e-06,
218
- "loss": 0.0,
219
- "step": 1500
220
- },
221
- {
222
- "epoch": 0.3537197626654496,
223
- "grad_norm": NaN,
224
- "learning_rate": 4.558780647442198e-06,
225
- "loss": 0.0,
226
- "step": 1550
227
- },
228
- {
229
- "epoch": 0.3651300775901415,
230
- "grad_norm": NaN,
231
- "learning_rate": 4.4931748357411275e-06,
232
- "loss": 0.0,
233
- "step": 1600
234
- },
235
- {
236
- "epoch": 0.3765403925148334,
237
- "grad_norm": NaN,
238
- "learning_rate": 4.423566477273245e-06,
239
- "loss": 0.0,
240
- "step": 1650
241
- },
242
- {
243
- "epoch": 0.3879507074395253,
244
- "grad_norm": NaN,
245
- "learning_rate": 4.350095354412442e-06,
246
- "loss": 0.0,
247
- "step": 1700
248
- },
249
- {
250
- "epoch": 0.3993610223642173,
251
- "grad_norm": NaN,
252
- "learning_rate": 4.272909006451306e-06,
253
- "loss": 0.0,
254
- "step": 1750
255
- },
256
- {
257
- "epoch": 0.4107713372889092,
258
- "grad_norm": NaN,
259
- "learning_rate": 4.192162433323576e-06,
260
- "loss": 0.0,
261
- "step": 1800
262
- },
263
- {
264
- "epoch": 0.4221816522136011,
265
- "grad_norm": NaN,
266
- "learning_rate": 4.10801778434471e-06,
267
- "loss": 0.0,
268
- "step": 1850
269
- },
270
- {
271
- "epoch": 0.433591967138293,
272
- "grad_norm": NaN,
273
- "learning_rate": 4.020644032595583e-06,
274
- "loss": 0.0,
275
- "step": 1900
276
- },
277
- {
278
- "epoch": 0.4450022820629849,
279
- "grad_norm": NaN,
280
- "learning_rate": 3.930216635603199e-06,
281
- "loss": 0.0,
282
- "step": 1950
283
- },
284
- {
285
- "epoch": 0.45641259698767683,
286
- "grad_norm": NaN,
287
- "learning_rate": 3.836917182999823e-06,
288
- "loss": 0.0,
289
- "step": 2000
290
- },
291
- {
292
- "epoch": 0.4678229119123688,
293
- "grad_norm": NaN,
294
- "learning_rate": 3.7409330318680704e-06,
295
- "loss": 0.0,
296
- "step": 2050
297
- },
298
- {
299
- "epoch": 0.4792332268370607,
300
- "grad_norm": NaN,
301
- "learning_rate": 3.64245693050422e-06,
302
- "loss": 0.0,
303
- "step": 2100
304
- },
305
- {
306
- "epoch": 0.4906435417617526,
307
- "grad_norm": NaN,
308
- "learning_rate": 3.5416866313553e-06,
309
- "loss": 0.0,
310
- "step": 2150
311
- },
312
- {
313
- "epoch": 0.5020538566864445,
314
- "grad_norm": NaN,
315
- "learning_rate": 3.4388244939072e-06,
316
- "loss": 0.0,
317
- "step": 2200
318
- },
319
- {
320
- "epoch": 0.5134641716111364,
321
- "grad_norm": NaN,
322
- "learning_rate": 3.3340770783212716e-06,
323
- "loss": 0.0,
324
- "step": 2250
325
- },
326
- {
327
- "epoch": 0.5248744865358284,
328
- "grad_norm": NaN,
329
- "learning_rate": 3.227654730635437e-06,
330
- "loss": 0.0,
331
- "step": 2300
332
- },
333
- {
334
- "epoch": 0.5362848014605203,
335
- "grad_norm": NaN,
336
- "learning_rate": 3.1197711603627844e-06,
337
- "loss": 0.0,
338
- "step": 2350
339
- },
340
- {
341
- "epoch": 0.5476951163852122,
342
- "grad_norm": NaN,
343
- "learning_rate": 3.0106430113358794e-06,
344
- "loss": 0.0,
345
- "step": 2400
346
- },
347
- {
348
- "epoch": 0.5591054313099042,
349
- "grad_norm": NaN,
350
- "learning_rate": 2.9004894266585893e-06,
351
- "loss": 0.0,
352
- "step": 2450
353
- },
354
- {
355
- "epoch": 0.5705157462345961,
356
- "grad_norm": NaN,
357
- "learning_rate": 2.78953160863906e-06,
358
- "loss": 0.0,
359
- "step": 2500
360
- },
361
- {
362
- "epoch": 0.581926061159288,
363
- "grad_norm": NaN,
364
- "learning_rate": 2.677992374587546e-06,
365
- "loss": 0.0,
366
- "step": 2550
367
- },
368
- {
369
- "epoch": 0.5933363760839799,
370
- "grad_norm": NaN,
371
- "learning_rate": 2.5660957093711147e-06,
372
- "loss": 0.0,
373
- "step": 2600
374
- },
375
- {
376
- "epoch": 0.6047466910086718,
377
- "grad_norm": NaN,
378
- "learning_rate": 2.4540663156237494e-06,
379
- "loss": 0.0,
380
- "step": 2650
381
- },
382
- {
383
- "epoch": 0.6161570059333638,
384
- "grad_norm": NaN,
385
- "learning_rate": 2.3421291625150825e-06,
386
- "loss": 0.0,
387
- "step": 2700
388
- },
389
- {
390
- "epoch": 0.6275673208580557,
391
- "grad_norm": NaN,
392
- "learning_rate": 2.2305090339838983e-06,
393
- "loss": 0.0,
394
- "step": 2750
395
- },
396
- {
397
- "epoch": 0.6389776357827476,
398
- "grad_norm": NaN,
399
- "learning_rate": 2.119430077343595e-06,
400
- "loss": 0.0,
401
- "step": 2800
402
- },
403
- {
404
- "epoch": 0.6503879507074395,
405
- "grad_norm": NaN,
406
- "learning_rate": 2.009115353166073e-06,
407
- "loss": 0.0,
408
- "step": 2850
409
- },
410
- {
411
- "epoch": 0.6617982656321314,
412
- "grad_norm": NaN,
413
- "learning_rate": 1.8997863873479453e-06,
414
- "loss": 0.0,
415
- "step": 2900
416
- },
417
- {
418
- "epoch": 0.6732085805568234,
419
- "grad_norm": NaN,
420
- "learning_rate": 1.7916627262585539e-06,
421
- "loss": 0.0,
422
- "step": 2950
423
- },
424
- {
425
- "epoch": 0.6846188954815153,
426
- "grad_norm": NaN,
427
- "learning_rate": 1.6849614958631432e-06,
428
- "loss": 0.0,
429
- "step": 3000
430
- },
431
- {
432
- "epoch": 0.6960292104062072,
433
- "grad_norm": NaN,
434
- "learning_rate": 1.579896965706499e-06,
435
- "loss": 0.0,
436
- "step": 3050
437
- },
438
- {
439
- "epoch": 0.7074395253308992,
440
- "grad_norm": NaN,
441
- "learning_rate": 1.476680118632648e-06,
442
- "loss": 0.0,
443
- "step": 3100
444
- },
445
- {
446
- "epoch": 0.7188498402555911,
447
- "grad_norm": NaN,
448
- "learning_rate": 1.375518227104661e-06,
449
- "loss": 0.0,
450
- "step": 3150
451
- },
452
- {
453
- "epoch": 0.730260155180283,
454
- "grad_norm": NaN,
455
- "learning_rate": 1.276614436975375e-06,
456
- "loss": 0.0,
457
- "step": 3200
458
- },
459
- {
460
- "epoch": 0.7416704701049749,
461
- "grad_norm": NaN,
462
- "learning_rate": 1.180167359544867e-06,
463
- "loss": 0.0,
464
- "step": 3250
465
- },
466
- {
467
- "epoch": 0.7530807850296668,
468
- "grad_norm": NaN,
469
- "learning_rate": 1.0863706727238841e-06,
470
- "loss": 0.0,
471
- "step": 3300
472
- },
473
- {
474
- "epoch": 0.7644910999543587,
475
- "grad_norm": NaN,
476
- "learning_rate": 9.95412732104138e-07,
477
- "loss": 0.0,
478
- "step": 3350
479
- },
480
- {
481
- "epoch": 0.7759014148790506,
482
- "grad_norm": NaN,
483
- "learning_rate": 9.074761927164958e-07,
484
- "loss": 0.0,
485
- "step": 3400
486
- },
487
- {
488
- "epoch": 0.7873117298037425,
489
- "grad_norm": NaN,
490
- "learning_rate": 8.227376422366091e-07,
491
- "loss": 0.0,
492
- "step": 3450
493
- },
494
- {
495
- "epoch": 0.7987220447284346,
496
- "grad_norm": NaN,
497
- "learning_rate": 7.413672463745617e-07,
498
- "loss": 0.0,
499
- "step": 3500
500
- },
501
- {
502
- "epoch": 0.8101323596531265,
503
- "grad_norm": NaN,
504
- "learning_rate": 6.635284071606391e-07,
505
- "loss": 0.0,
506
- "step": 3550
507
- },
508
- {
509
- "epoch": 0.8215426745778184,
510
- "grad_norm": NaN,
511
- "learning_rate": 5.89377434813414e-07,
512
- "loss": 0.0,
513
- "step": 3600
514
- },
515
- {
516
- "epoch": 0.8329529895025103,
517
- "grad_norm": NaN,
518
- "learning_rate": 5.190632338490883e-07,
519
- "loss": 0.0,
520
- "step": 3650
521
- },
522
- {
523
- "epoch": 0.8443633044272022,
524
- "grad_norm": NaN,
525
- "learning_rate": 4.5272700406242626e-07,
526
- "loss": 0.0,
527
- "step": 3700
528
- },
529
- {
530
- "epoch": 0.8557736193518941,
531
- "grad_norm": NaN,
532
- "learning_rate": 3.9050195697972776e-07,
533
- "loss": 0.0,
534
- "step": 3750
535
- },
536
- {
537
- "epoch": 0.867183934276586,
538
- "grad_norm": NaN,
539
- "learning_rate": 3.325130483532671e-07,
540
- "loss": 0.0,
541
- "step": 3800
542
- },
543
- {
544
- "epoch": 0.8785942492012779,
545
- "grad_norm": NaN,
546
- "learning_rate": 2.788767272343648e-07,
547
- "loss": 0.0,
548
- "step": 3850
549
- },
550
- {
551
- "epoch": 0.8900045641259698,
552
- "grad_norm": NaN,
553
- "learning_rate": 2.2970070212898126e-07,
554
- "loss": 0.0,
555
- "step": 3900
556
- },
557
- {
558
- "epoch": 0.9014148790506618,
559
- "grad_norm": NaN,
560
- "learning_rate": 1.8508372470544045e-07,
561
- "loss": 0.0,
562
- "step": 3950
563
- },
564
- {
565
- "epoch": 0.9128251939753537,
566
- "grad_norm": NaN,
567
- "learning_rate": 1.4511539148860805e-07,
568
- "loss": 0.0,
569
- "step": 4000
570
- },
571
- {
572
- "epoch": 0.9242355089000457,
573
- "grad_norm": NaN,
574
- "learning_rate": 1.0987596393875477e-07,
575
- "loss": 0.0,
576
- "step": 4050
577
- },
578
- {
579
- "epoch": 0.9356458238247376,
580
- "grad_norm": NaN,
581
- "learning_rate": 7.943620727641016e-08,
582
- "loss": 0.0,
583
- "step": 4100
584
- },
585
- {
586
- "epoch": 0.9470561387494295,
587
- "grad_norm": NaN,
588
- "learning_rate": 5.385724837686124e-08,
589
- "loss": 0.0,
590
- "step": 4150
591
- },
592
- {
593
- "epoch": 0.9584664536741214,
594
- "grad_norm": NaN,
595
- "learning_rate": 3.3190453019670835e-08,
596
- "loss": 0.0,
597
- "step": 4200
598
- },
599
- {
600
- "epoch": 0.9698767685988133,
601
- "grad_norm": NaN,
602
- "learning_rate": 1.7477322739704038e-08,
603
- "loss": 0.0,
604
- "step": 4250
605
- },
606
- {
607
- "epoch": 0.9812870835235052,
608
- "grad_norm": NaN,
609
- "learning_rate": 6.749411486805246e-09,
610
- "loss": 0.0,
611
- "step": 4300
612
- },
613
- {
614
- "epoch": 0.9926973984481972,
615
- "grad_norm": NaN,
616
- "learning_rate": 1.028262261483226e-09,
617
- "loss": 0.0,
618
- "step": 4350
619
- },
620
  {
621
  "epoch": 1.0,
622
- "step": 4382,
623
- "total_flos": 8.07158446678868e+17,
624
- "train_loss": 0.007153803548112083,
625
- "train_runtime": 33886.5214,
626
- "train_samples_per_second": 0.517,
627
- "train_steps_per_second": 0.129
628
  }
629
  ],
630
  "logging_steps": 50,
631
- "max_steps": 4382,
632
  "num_input_tokens_seen": 0,
633
  "num_train_epochs": 1,
634
  "save_steps": 500,
@@ -638,13 +50,13 @@
638
  "should_epoch_stop": false,
639
  "should_evaluate": false,
640
  "should_log": false,
641
- "should_save": true,
642
  "should_training_stop": false
643
  },
644
  "attributes": {}
645
  }
646
  },
647
- "total_flos": 8.07158446678868e+17,
648
  "train_batch_size": 4,
649
  "trial_name": null,
650
  "trial_params": null
 
3
  "best_model_checkpoint": null,
4
  "epoch": 1.0,
5
  "eval_steps": 500,
6
+ "global_step": 170,
7
  "is_hyper_param_search": false,
8
  "is_local_process_zero": true,
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
+ "epoch": 0.29411764705882354,
13
  "grad_norm": NaN,
14
+ "learning_rate": 4.83118057351089e-06,
15
+ "loss": 0.6582,
16
  "step": 50
17
  },
18
  {
19
+ "epoch": 0.5882352941176471,
20
  "grad_norm": NaN,
21
+ "learning_rate": 2.6154586466143495e-06,
22
  "loss": 0.0,
23
  "step": 100
24
  },
25
  {
26
+ "epoch": 0.8823529411764706,
27
  "grad_norm": NaN,
28
+ "learning_rate": 2.620917716123444e-07,
29
  "loss": 0.0,
30
  "step": 150
31
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
32
  {
33
  "epoch": 1.0,
34
+ "step": 170,
35
+ "total_flos": 3.1269503354535936e+16,
36
+ "train_loss": 0.19359449498793657,
37
+ "train_runtime": 1514.0603,
38
+ "train_samples_per_second": 0.448,
39
+ "train_steps_per_second": 0.112
40
  }
41
  ],
42
  "logging_steps": 50,
43
+ "max_steps": 170,
44
  "num_input_tokens_seen": 0,
45
  "num_train_epochs": 1,
46
  "save_steps": 500,
 
50
  "should_epoch_stop": false,
51
  "should_evaluate": false,
52
  "should_log": false,
53
+ "should_save": false,
54
  "should_training_stop": false
55
  },
56
  "attributes": {}
57
  }
58
  },
59
+ "total_flos": 3.1269503354535936e+16,
60
  "train_batch_size": 4,
61
  "trial_name": null,
62
  "trial_params": null
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:84f5723d98d57d4f6ca9ab561ecca9634d9bd8b4d920d8415fb13f4cb95f33d4
3
  size 5112
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4844ff749272ef526f5f855db84ae0970596b037c1465ab89ba72153131c3b54
3
  size 5112