medxiaorudan commited on
Commit
2a5ba1f
1 Parent(s): cfb75db

Upload 8 files

Browse files
README.md CHANGED
@@ -1,6 +1,204 @@
1
  ---
2
- license: llama2
3
- pipeline_tag: text-generation
4
- tags:
5
- - code
6
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ library_name: peft
3
+ base_model: codellama/CodeLlama-7b-hf
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
+
201
+
202
+ ### Framework versions
203
+
204
+ - PEFT 0.7.1
adapter_config.json ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "codellama/CodeLlama-7b-hf",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "loftq_config": {},
12
+ "lora_alpha": 16,
13
+ "lora_dropout": 0.1,
14
+ "megatron_config": null,
15
+ "megatron_core": "megatron.core",
16
+ "modules_to_save": null,
17
+ "peft_type": "LORA",
18
+ "r": 16,
19
+ "rank_pattern": {},
20
+ "revision": null,
21
+ "target_modules": [
22
+ "q_proj",
23
+ "v_proj"
24
+ ],
25
+ "task_type": "CAUSAL_LM"
26
+ }
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7eaa51169fb5f5f33b328f26090dcd19a47bde0a9efe64e78856dbbe04a07e7a
3
+ size 888
optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e5a58a4b4482c792973c85888844ab6f0ccef01323f5d67f16a3ed6b764ca1f4
3
+ size 67217018
rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8bc6f074c7b85448f6f01a3a5d20bd44a43e5cceb5263586be313386dfd35489
3
+ size 14244
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ee665d99b8d4ac37b6829a57abd01a01763b04846f27bc645d525d70173d6821
3
+ size 1064
trainer_state.json ADDED
@@ -0,0 +1,419 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 5.797101449275362,
5
+ "eval_steps": 20,
6
+ "global_step": 400,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.14,
13
+ "learning_rate": 2.9999999999999997e-05,
14
+ "loss": 1.4612,
15
+ "step": 10
16
+ },
17
+ {
18
+ "epoch": 0.29,
19
+ "learning_rate": 5.9999999999999995e-05,
20
+ "loss": 1.6819,
21
+ "step": 20
22
+ },
23
+ {
24
+ "epoch": 0.29,
25
+ "eval_loss": 1.493472933769226,
26
+ "eval_runtime": 146.9486,
27
+ "eval_samples_per_second": 6.669,
28
+ "eval_steps_per_second": 0.837,
29
+ "step": 20
30
+ },
31
+ {
32
+ "epoch": 0.43,
33
+ "learning_rate": 8.999999999999999e-05,
34
+ "loss": 1.3849,
35
+ "step": 30
36
+ },
37
+ {
38
+ "epoch": 0.58,
39
+ "learning_rate": 0.00011999999999999999,
40
+ "loss": 1.3102,
41
+ "step": 40
42
+ },
43
+ {
44
+ "epoch": 0.58,
45
+ "eval_loss": 1.0922572612762451,
46
+ "eval_runtime": 146.6688,
47
+ "eval_samples_per_second": 6.682,
48
+ "eval_steps_per_second": 0.839,
49
+ "step": 40
50
+ },
51
+ {
52
+ "epoch": 0.72,
53
+ "learning_rate": 0.00015,
54
+ "loss": 0.9074,
55
+ "step": 50
56
+ },
57
+ {
58
+ "epoch": 0.87,
59
+ "learning_rate": 0.00017999999999999998,
60
+ "loss": 0.8606,
61
+ "step": 60
62
+ },
63
+ {
64
+ "epoch": 0.87,
65
+ "eval_loss": 0.7950681447982788,
66
+ "eval_runtime": 147.0034,
67
+ "eval_samples_per_second": 6.667,
68
+ "eval_steps_per_second": 0.837,
69
+ "step": 60
70
+ },
71
+ {
72
+ "epoch": 1.01,
73
+ "learning_rate": 0.00020999999999999998,
74
+ "loss": 0.7308,
75
+ "step": 70
76
+ },
77
+ {
78
+ "epoch": 1.16,
79
+ "learning_rate": 0.00023999999999999998,
80
+ "loss": 0.769,
81
+ "step": 80
82
+ },
83
+ {
84
+ "epoch": 1.16,
85
+ "eval_loss": 0.7387300729751587,
86
+ "eval_runtime": 146.9341,
87
+ "eval_samples_per_second": 6.67,
88
+ "eval_steps_per_second": 0.837,
89
+ "step": 80
90
+ },
91
+ {
92
+ "epoch": 1.3,
93
+ "learning_rate": 0.00027,
94
+ "loss": 0.7344,
95
+ "step": 90
96
+ },
97
+ {
98
+ "epoch": 1.45,
99
+ "learning_rate": 0.0003,
100
+ "loss": 0.6724,
101
+ "step": 100
102
+ },
103
+ {
104
+ "epoch": 1.45,
105
+ "eval_loss": 0.7141170501708984,
106
+ "eval_runtime": 146.8124,
107
+ "eval_samples_per_second": 6.675,
108
+ "eval_steps_per_second": 0.838,
109
+ "step": 100
110
+ },
111
+ {
112
+ "epoch": 1.59,
113
+ "learning_rate": 0.00029,
114
+ "loss": 0.7295,
115
+ "step": 110
116
+ },
117
+ {
118
+ "epoch": 1.74,
119
+ "learning_rate": 0.00028,
120
+ "loss": 0.6233,
121
+ "step": 120
122
+ },
123
+ {
124
+ "epoch": 1.74,
125
+ "eval_loss": 0.6994462013244629,
126
+ "eval_runtime": 146.8753,
127
+ "eval_samples_per_second": 6.672,
128
+ "eval_steps_per_second": 0.837,
129
+ "step": 120
130
+ },
131
+ {
132
+ "epoch": 1.88,
133
+ "learning_rate": 0.00027,
134
+ "loss": 0.7352,
135
+ "step": 130
136
+ },
137
+ {
138
+ "epoch": 2.03,
139
+ "learning_rate": 0.00026,
140
+ "loss": 0.6463,
141
+ "step": 140
142
+ },
143
+ {
144
+ "epoch": 2.03,
145
+ "eval_loss": 0.6910027861595154,
146
+ "eval_runtime": 147.0376,
147
+ "eval_samples_per_second": 6.665,
148
+ "eval_steps_per_second": 0.837,
149
+ "step": 140
150
+ },
151
+ {
152
+ "epoch": 2.17,
153
+ "learning_rate": 0.00025,
154
+ "loss": 0.6765,
155
+ "step": 150
156
+ },
157
+ {
158
+ "epoch": 2.32,
159
+ "learning_rate": 0.00023999999999999998,
160
+ "loss": 0.683,
161
+ "step": 160
162
+ },
163
+ {
164
+ "epoch": 2.32,
165
+ "eval_loss": 0.6793327331542969,
166
+ "eval_runtime": 147.9244,
167
+ "eval_samples_per_second": 6.625,
168
+ "eval_steps_per_second": 0.832,
169
+ "step": 160
170
+ },
171
+ {
172
+ "epoch": 2.46,
173
+ "learning_rate": 0.00023,
174
+ "loss": 0.6206,
175
+ "step": 170
176
+ },
177
+ {
178
+ "epoch": 2.61,
179
+ "learning_rate": 0.00021999999999999995,
180
+ "loss": 0.7008,
181
+ "step": 180
182
+ },
183
+ {
184
+ "epoch": 2.61,
185
+ "eval_loss": 0.6654186248779297,
186
+ "eval_runtime": 147.0825,
187
+ "eval_samples_per_second": 6.663,
188
+ "eval_steps_per_second": 0.836,
189
+ "step": 180
190
+ },
191
+ {
192
+ "epoch": 2.75,
193
+ "learning_rate": 0.00020999999999999998,
194
+ "loss": 0.5981,
195
+ "step": 190
196
+ },
197
+ {
198
+ "epoch": 2.9,
199
+ "learning_rate": 0.00019999999999999998,
200
+ "loss": 0.6754,
201
+ "step": 200
202
+ },
203
+ {
204
+ "epoch": 2.9,
205
+ "eval_loss": 0.6593416929244995,
206
+ "eval_runtime": 146.8493,
207
+ "eval_samples_per_second": 6.674,
208
+ "eval_steps_per_second": 0.838,
209
+ "step": 200
210
+ },
211
+ {
212
+ "epoch": 3.04,
213
+ "learning_rate": 0.00018999999999999998,
214
+ "loss": 0.6217,
215
+ "step": 210
216
+ },
217
+ {
218
+ "epoch": 3.19,
219
+ "learning_rate": 0.00017999999999999998,
220
+ "loss": 0.6349,
221
+ "step": 220
222
+ },
223
+ {
224
+ "epoch": 3.19,
225
+ "eval_loss": 0.6553820967674255,
226
+ "eval_runtime": 146.9525,
227
+ "eval_samples_per_second": 6.669,
228
+ "eval_steps_per_second": 0.837,
229
+ "step": 220
230
+ },
231
+ {
232
+ "epoch": 3.33,
233
+ "learning_rate": 0.00016999999999999999,
234
+ "loss": 0.6592,
235
+ "step": 230
236
+ },
237
+ {
238
+ "epoch": 3.48,
239
+ "learning_rate": 0.00015999999999999999,
240
+ "loss": 0.5813,
241
+ "step": 240
242
+ },
243
+ {
244
+ "epoch": 3.48,
245
+ "eval_loss": 0.6516290307044983,
246
+ "eval_runtime": 147.0111,
247
+ "eval_samples_per_second": 6.666,
248
+ "eval_steps_per_second": 0.837,
249
+ "step": 240
250
+ },
251
+ {
252
+ "epoch": 3.62,
253
+ "learning_rate": 0.00015,
254
+ "loss": 0.6827,
255
+ "step": 250
256
+ },
257
+ {
258
+ "epoch": 3.77,
259
+ "learning_rate": 0.00014,
260
+ "loss": 0.6018,
261
+ "step": 260
262
+ },
263
+ {
264
+ "epoch": 3.77,
265
+ "eval_loss": 0.6494865417480469,
266
+ "eval_runtime": 146.9051,
267
+ "eval_samples_per_second": 6.671,
268
+ "eval_steps_per_second": 0.837,
269
+ "step": 260
270
+ },
271
+ {
272
+ "epoch": 3.91,
273
+ "learning_rate": 0.00013,
274
+ "loss": 0.6457,
275
+ "step": 270
276
+ },
277
+ {
278
+ "epoch": 4.06,
279
+ "learning_rate": 0.00011999999999999999,
280
+ "loss": 0.644,
281
+ "step": 280
282
+ },
283
+ {
284
+ "epoch": 4.06,
285
+ "eval_loss": 0.6468493342399597,
286
+ "eval_runtime": 146.9249,
287
+ "eval_samples_per_second": 6.67,
288
+ "eval_steps_per_second": 0.837,
289
+ "step": 280
290
+ },
291
+ {
292
+ "epoch": 4.2,
293
+ "learning_rate": 0.00010999999999999998,
294
+ "loss": 0.5954,
295
+ "step": 290
296
+ },
297
+ {
298
+ "epoch": 4.35,
299
+ "learning_rate": 9.999999999999999e-05,
300
+ "loss": 0.6548,
301
+ "step": 300
302
+ },
303
+ {
304
+ "epoch": 4.35,
305
+ "eval_loss": 0.6439973711967468,
306
+ "eval_runtime": 146.9023,
307
+ "eval_samples_per_second": 6.671,
308
+ "eval_steps_per_second": 0.837,
309
+ "step": 300
310
+ },
311
+ {
312
+ "epoch": 4.49,
313
+ "learning_rate": 8.999999999999999e-05,
314
+ "loss": 0.5504,
315
+ "step": 310
316
+ },
317
+ {
318
+ "epoch": 4.64,
319
+ "learning_rate": 7.999999999999999e-05,
320
+ "loss": 0.6869,
321
+ "step": 320
322
+ },
323
+ {
324
+ "epoch": 4.64,
325
+ "eval_loss": 0.6418542861938477,
326
+ "eval_runtime": 146.8382,
327
+ "eval_samples_per_second": 6.674,
328
+ "eval_steps_per_second": 0.838,
329
+ "step": 320
330
+ },
331
+ {
332
+ "epoch": 4.78,
333
+ "learning_rate": 7e-05,
334
+ "loss": 0.6151,
335
+ "step": 330
336
+ },
337
+ {
338
+ "epoch": 4.93,
339
+ "learning_rate": 5.9999999999999995e-05,
340
+ "loss": 0.6089,
341
+ "step": 340
342
+ },
343
+ {
344
+ "epoch": 4.93,
345
+ "eval_loss": 0.6405566334724426,
346
+ "eval_runtime": 146.9207,
347
+ "eval_samples_per_second": 6.67,
348
+ "eval_steps_per_second": 0.837,
349
+ "step": 340
350
+ },
351
+ {
352
+ "epoch": 5.07,
353
+ "learning_rate": 4.9999999999999996e-05,
354
+ "loss": 0.6438,
355
+ "step": 350
356
+ },
357
+ {
358
+ "epoch": 5.22,
359
+ "learning_rate": 3.9999999999999996e-05,
360
+ "loss": 0.577,
361
+ "step": 360
362
+ },
363
+ {
364
+ "epoch": 5.22,
365
+ "eval_loss": 0.6396059393882751,
366
+ "eval_runtime": 146.9947,
367
+ "eval_samples_per_second": 6.667,
368
+ "eval_steps_per_second": 0.837,
369
+ "step": 360
370
+ },
371
+ {
372
+ "epoch": 5.36,
373
+ "learning_rate": 2.9999999999999997e-05,
374
+ "loss": 0.6599,
375
+ "step": 370
376
+ },
377
+ {
378
+ "epoch": 5.51,
379
+ "learning_rate": 1.9999999999999998e-05,
380
+ "loss": 0.5724,
381
+ "step": 380
382
+ },
383
+ {
384
+ "epoch": 5.51,
385
+ "eval_loss": 0.6387772560119629,
386
+ "eval_runtime": 146.77,
387
+ "eval_samples_per_second": 6.677,
388
+ "eval_steps_per_second": 0.838,
389
+ "step": 380
390
+ },
391
+ {
392
+ "epoch": 5.65,
393
+ "learning_rate": 9.999999999999999e-06,
394
+ "loss": 0.6487,
395
+ "step": 390
396
+ },
397
+ {
398
+ "epoch": 5.8,
399
+ "learning_rate": 0.0,
400
+ "loss": 0.6236,
401
+ "step": 400
402
+ },
403
+ {
404
+ "epoch": 5.8,
405
+ "eval_loss": 0.6381928324699402,
406
+ "eval_runtime": 146.9718,
407
+ "eval_samples_per_second": 6.668,
408
+ "eval_steps_per_second": 0.837,
409
+ "step": 400
410
+ }
411
+ ],
412
+ "logging_steps": 10,
413
+ "max_steps": 400,
414
+ "num_train_epochs": 6,
415
+ "save_steps": 20,
416
+ "total_flos": 7.971097386781901e+17,
417
+ "trial_name": null,
418
+ "trial_params": null
419
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4a7c0f88fa63ad01ffb4c6e2153d96f064ad7c39ac3df8a92243b741310a0d1c
3
+ size 4472