bimabk commited on
Commit
9c645d8
·
verified ·
1 Parent(s): 13f7a53

Upload task output 0fe99f84-0038-4cec-8e61-1eb9fea8dc55

Browse files
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: None
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": null,
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": "gaussian",
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
+ "o_proj",
28
+ "v_proj",
29
+ "down_proj",
30
+ "q_proj",
31
+ "up_proj",
32
+ "gate_proj",
33
+ "k_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 sha256:3319fe13ad42d192b8d7b5cd16c70b7ec33c93442bbb18994e4f4a4348c4585c
3
+ size 778096664
loss.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ 280,1.8434581756591797
trainer_state.json ADDED
@@ -0,0 +1,450 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": 280,
3
+ "best_metric": 1.8434581756591797,
4
+ "best_model_checkpoint": "/workspace/scripts/soutputs/0fe99f84-0038-4cec-8e61-1eb9fea8dc55_8/checkpoint-280",
5
+ "epoch": 2.0,
6
+ "eval_steps": 500,
7
+ "global_step": 280,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.03571428571428571,
14
+ "grad_norm": 8.88685131072998,
15
+ "learning_rate": 1.7366143371721805e-05,
16
+ "loss": 4.6453,
17
+ "step": 5
18
+ },
19
+ {
20
+ "epoch": 0.07142857142857142,
21
+ "grad_norm": 4.32283353805542,
22
+ "learning_rate": 3.907382258637406e-05,
23
+ "loss": 3.599,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.10714285714285714,
28
+ "grad_norm": 3.268484592437744,
29
+ "learning_rate": 6.078150180102633e-05,
30
+ "loss": 3.1074,
31
+ "step": 15
32
+ },
33
+ {
34
+ "epoch": 0.14285714285714285,
35
+ "grad_norm": 2.8239047527313232,
36
+ "learning_rate": 8.248918101567858e-05,
37
+ "loss": 2.8444,
38
+ "step": 20
39
+ },
40
+ {
41
+ "epoch": 0.17857142857142858,
42
+ "grad_norm": 3.067504644393921,
43
+ "learning_rate": 0.00010419686023033085,
44
+ "loss": 2.6663,
45
+ "step": 25
46
+ },
47
+ {
48
+ "epoch": 0.21428571428571427,
49
+ "grad_norm": 2.57623553276062,
50
+ "learning_rate": 0.0001259045394449831,
51
+ "loss": 2.5882,
52
+ "step": 30
53
+ },
54
+ {
55
+ "epoch": 0.25,
56
+ "grad_norm": 2.359346628189087,
57
+ "learning_rate": 0.00014761221865963536,
58
+ "loss": 2.5005,
59
+ "step": 35
60
+ },
61
+ {
62
+ "epoch": 0.2857142857142857,
63
+ "grad_norm": 2.330860137939453,
64
+ "learning_rate": 0.00015192340354349201,
65
+ "loss": 2.4555,
66
+ "step": 40
67
+ },
68
+ {
69
+ "epoch": 0.32142857142857145,
70
+ "grad_norm": 2.0505852699279785,
71
+ "learning_rate": 0.0001518001581828618,
72
+ "loss": 2.3906,
73
+ "step": 45
74
+ },
75
+ {
76
+ "epoch": 0.35714285714285715,
77
+ "grad_norm": 1.8215535879135132,
78
+ "learning_rate": 0.00015158232645757987,
79
+ "loss": 2.3629,
80
+ "step": 50
81
+ },
82
+ {
83
+ "epoch": 0.39285714285714285,
84
+ "grad_norm": 1.6129544973373413,
85
+ "learning_rate": 0.0001512702709270553,
86
+ "loss": 2.3095,
87
+ "step": 55
88
+ },
89
+ {
90
+ "epoch": 0.42857142857142855,
91
+ "grad_norm": 1.5386137962341309,
92
+ "learning_rate": 0.00015086451097692214,
93
+ "loss": 2.2798,
94
+ "step": 60
95
+ },
96
+ {
97
+ "epoch": 0.4642857142857143,
98
+ "grad_norm": 1.697199821472168,
99
+ "learning_rate": 0.00015036572195457326,
100
+ "loss": 2.2578,
101
+ "step": 65
102
+ },
103
+ {
104
+ "epoch": 0.5,
105
+ "grad_norm": 1.7271143198013306,
106
+ "learning_rate": 0.00014977473404511135,
107
+ "loss": 2.2371,
108
+ "step": 70
109
+ },
110
+ {
111
+ "epoch": 0.5357142857142857,
112
+ "grad_norm": 1.7022008895874023,
113
+ "learning_rate": 0.00014909253088958753,
114
+ "loss": 2.2332,
115
+ "step": 75
116
+ },
117
+ {
118
+ "epoch": 0.5714285714285714,
119
+ "grad_norm": 1.5951184034347534,
120
+ "learning_rate": 0.00014832024794782817,
121
+ "loss": 2.1967,
122
+ "step": 80
123
+ },
124
+ {
125
+ "epoch": 0.6071428571428571,
126
+ "grad_norm": 1.5995818376541138,
127
+ "learning_rate": 0.00014745917060857383,
128
+ "loss": 2.1501,
129
+ "step": 85
130
+ },
131
+ {
132
+ "epoch": 0.6428571428571429,
133
+ "grad_norm": 1.3882001638412476,
134
+ "learning_rate": 0.0001465107320500767,
135
+ "loss": 2.1184,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 0.6785714285714286,
140
+ "grad_norm": 1.4893513917922974,
141
+ "learning_rate": 0.00014547651085471683,
142
+ "loss": 2.1836,
143
+ "step": 95
144
+ },
145
+ {
146
+ "epoch": 0.7142857142857143,
147
+ "grad_norm": 1.5417523384094238,
148
+ "learning_rate": 0.0001443582283816074,
149
+ "loss": 2.1532,
150
+ "step": 100
151
+ },
152
+ {
153
+ "epoch": 0.75,
154
+ "grad_norm": 1.474676251411438,
155
+ "learning_rate": 0.0001431577459015626,
156
+ "loss": 2.1411,
157
+ "step": 105
158
+ },
159
+ {
160
+ "epoch": 0.7857142857142857,
161
+ "grad_norm": 1.6343954801559448,
162
+ "learning_rate": 0.00014187706149919582,
163
+ "loss": 2.1325,
164
+ "step": 110
165
+ },
166
+ {
167
+ "epoch": 0.8214285714285714,
168
+ "grad_norm": 1.6139814853668213,
169
+ "learning_rate": 0.00014051830674730509,
170
+ "loss": 2.1292,
171
+ "step": 115
172
+ },
173
+ {
174
+ "epoch": 0.8571428571428571,
175
+ "grad_norm": 1.4923847913742065,
176
+ "learning_rate": 0.00013908374315908066,
177
+ "loss": 2.1303,
178
+ "step": 120
179
+ },
180
+ {
181
+ "epoch": 0.8928571428571429,
182
+ "grad_norm": 1.425238013267517,
183
+ "learning_rate": 0.00013757575842403914,
184
+ "loss": 2.0619,
185
+ "step": 125
186
+ },
187
+ {
188
+ "epoch": 0.9285714285714286,
189
+ "grad_norm": 1.3964207172393799,
190
+ "learning_rate": 0.0001359968624339503,
191
+ "loss": 2.0931,
192
+ "step": 130
193
+ },
194
+ {
195
+ "epoch": 0.9642857142857143,
196
+ "grad_norm": 1.4556257724761963,
197
+ "learning_rate": 0.0001343496831053697,
198
+ "loss": 2.0685,
199
+ "step": 135
200
+ },
201
+ {
202
+ "epoch": 1.0,
203
+ "grad_norm": 1.4229402542114258,
204
+ "learning_rate": 0.00013263696200573104,
205
+ "loss": 2.1007,
206
+ "step": 140
207
+ },
208
+ {
209
+ "epoch": 1.0,
210
+ "eval_loss": 1.9944559335708618,
211
+ "eval_runtime": 0.6316,
212
+ "eval_samples_per_second": 7.916,
213
+ "eval_steps_per_second": 7.916,
214
+ "step": 140
215
+ },
216
+ {
217
+ "epoch": 1.0,
218
+ "eval_loss": 1.9944559335708618,
219
+ "eval_runtime": 0.5923,
220
+ "eval_samples_per_second": 8.442,
221
+ "eval_steps_per_second": 8.442,
222
+ "step": 140
223
+ },
224
+ {
225
+ "epoch": 1.0357142857142858,
226
+ "grad_norm": 1.4764453172683716,
227
+ "learning_rate": 0.00013086154979027761,
228
+ "loss": 1.7993,
229
+ "step": 145
230
+ },
231
+ {
232
+ "epoch": 1.0714285714285714,
233
+ "grad_norm": 1.437887191772461,
234
+ "learning_rate": 0.0001290264014574281,
235
+ "loss": 1.7982,
236
+ "step": 150
237
+ },
238
+ {
239
+ "epoch": 1.1071428571428572,
240
+ "grad_norm": 1.459887146949768,
241
+ "learning_rate": 0.0001271345714304733,
242
+ "loss": 1.7868,
243
+ "step": 155
244
+ },
245
+ {
246
+ "epoch": 1.1428571428571428,
247
+ "grad_norm": 1.4325443506240845,
248
+ "learning_rate": 0.0001251892084737899,
249
+ "loss": 1.7632,
250
+ "step": 160
251
+ },
252
+ {
253
+ "epoch": 1.1785714285714286,
254
+ "grad_norm": 1.3728995323181152,
255
+ "learning_rate": 0.0001231935504520331,
256
+ "loss": 1.7354,
257
+ "step": 165
258
+ },
259
+ {
260
+ "epoch": 1.2142857142857142,
261
+ "grad_norm": 1.3899074792861938,
262
+ "learning_rate": 0.00012115091894103025,
263
+ "loss": 1.7969,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 1.25,
268
+ "grad_norm": 1.4964189529418945,
269
+ "learning_rate": 0.00011906471369934588,
270
+ "loss": 1.7801,
271
+ "step": 175
272
+ },
273
+ {
274
+ "epoch": 1.2857142857142856,
275
+ "grad_norm": 1.3325155973434448,
276
+ "learning_rate": 0.00011693840700971884,
277
+ "loss": 1.7869,
278
+ "step": 180
279
+ },
280
+ {
281
+ "epoch": 1.3214285714285714,
282
+ "grad_norm": 1.488095998764038,
283
+ "learning_rate": 0.00011477553789979063,
284
+ "loss": 1.7771,
285
+ "step": 185
286
+ },
287
+ {
288
+ "epoch": 1.3571428571428572,
289
+ "grad_norm": 1.3599910736083984,
290
+ "learning_rate": 0.00011257970625174295,
291
+ "loss": 1.7807,
292
+ "step": 190
293
+ },
294
+ {
295
+ "epoch": 1.3928571428571428,
296
+ "grad_norm": 1.425702452659607,
297
+ "learning_rate": 0.0001103545668106492,
298
+ "loss": 1.8142,
299
+ "step": 195
300
+ },
301
+ {
302
+ "epoch": 1.4285714285714286,
303
+ "grad_norm": 1.4276255369186401,
304
+ "learning_rate": 0.00010810382310151192,
305
+ "loss": 1.7576,
306
+ "step": 200
307
+ },
308
+ {
309
+ "epoch": 1.4642857142857144,
310
+ "grad_norm": 1.3717377185821533,
311
+ "learning_rate": 0.00010583122126511095,
312
+ "loss": 1.7512,
313
+ "step": 205
314
+ },
315
+ {
316
+ "epoch": 1.5,
317
+ "grad_norm": 1.3083884716033936,
318
+ "learning_rate": 0.00010354054382292182,
319
+ "loss": 1.7535,
320
+ "step": 210
321
+ },
322
+ {
323
+ "epoch": 1.5357142857142856,
324
+ "grad_norm": 1.3747572898864746,
325
+ "learning_rate": 0.00010123560338148197,
326
+ "loss": 1.8019,
327
+ "step": 215
328
+ },
329
+ {
330
+ "epoch": 1.5714285714285714,
331
+ "grad_norm": 1.3702155351638794,
332
+ "learning_rate": 9.892023628668355e-05,
333
+ "loss": 1.7736,
334
+ "step": 220
335
+ },
336
+ {
337
+ "epoch": 1.6071428571428572,
338
+ "grad_norm": 1.3148250579833984,
339
+ "learning_rate": 9.659829623855417e-05,
340
+ "loss": 1.747,
341
+ "step": 225
342
+ },
343
+ {
344
+ "epoch": 1.6428571428571428,
345
+ "grad_norm": 1.3732651472091675,
346
+ "learning_rate": 9.42736478771537e-05,
347
+ "loss": 1.7581,
348
+ "step": 230
349
+ },
350
+ {
351
+ "epoch": 1.6785714285714286,
352
+ "grad_norm": 1.2940075397491455,
353
+ "learning_rate": 9.1950160350262e-05,
354
+ "loss": 1.7153,
355
+ "step": 235
356
+ },
357
+ {
358
+ "epoch": 1.7142857142857144,
359
+ "grad_norm": 1.3065768480300903,
360
+ "learning_rate": 8.963170087356454e-05,
361
+ "loss": 1.7284,
362
+ "step": 240
363
+ },
364
+ {
365
+ "epoch": 1.75,
366
+ "grad_norm": 1.3015515804290771,
367
+ "learning_rate": 8.732212829405351e-05,
368
+ "loss": 1.7104,
369
+ "step": 245
370
+ },
371
+ {
372
+ "epoch": 1.7857142857142856,
373
+ "grad_norm": 1.320367693901062,
374
+ "learning_rate": 8.502528666735768e-05,
375
+ "loss": 1.7164,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 1.8214285714285714,
380
+ "grad_norm": 1.328780174255371,
381
+ "learning_rate": 8.27449988596913e-05,
382
+ "loss": 1.6933,
383
+ "step": 255
384
+ },
385
+ {
386
+ "epoch": 1.8571428571428572,
387
+ "grad_norm": 1.2614611387252808,
388
+ "learning_rate": 8.048506018507052e-05,
389
+ "loss": 1.7327,
390
+ "step": 260
391
+ },
392
+ {
393
+ "epoch": 1.8928571428571428,
394
+ "grad_norm": 1.3493170738220215,
395
+ "learning_rate": 7.824923208838779e-05,
396
+ "loss": 1.7301,
397
+ "step": 265
398
+ },
399
+ {
400
+ "epoch": 1.9285714285714286,
401
+ "grad_norm": 1.33063542842865,
402
+ "learning_rate": 7.604123588485805e-05,
403
+ "loss": 1.6979,
404
+ "step": 270
405
+ },
406
+ {
407
+ "epoch": 1.9642857142857144,
408
+ "grad_norm": 1.3395414352416992,
409
+ "learning_rate": 7.386474656625674e-05,
410
+ "loss": 1.7222,
411
+ "step": 275
412
+ },
413
+ {
414
+ "epoch": 2.0,
415
+ "grad_norm": 1.3347551822662354,
416
+ "learning_rate": 7.17233866842588e-05,
417
+ "loss": 1.7162,
418
+ "step": 280
419
+ },
420
+ {
421
+ "epoch": 2.0,
422
+ "eval_loss": 1.8434581756591797,
423
+ "eval_runtime": 0.6338,
424
+ "eval_samples_per_second": 7.889,
425
+ "eval_steps_per_second": 7.889,
426
+ "step": 280
427
+ }
428
+ ],
429
+ "logging_steps": 5,
430
+ "max_steps": 420,
431
+ "num_input_tokens_seen": 0,
432
+ "num_train_epochs": 3,
433
+ "save_steps": 500,
434
+ "stateful_callbacks": {
435
+ "TrainerControl": {
436
+ "args": {
437
+ "should_epoch_stop": false,
438
+ "should_evaluate": false,
439
+ "should_log": false,
440
+ "should_save": true,
441
+ "should_training_stop": false
442
+ },
443
+ "attributes": {}
444
+ }
445
+ },
446
+ "total_flos": 4.976417678819328e+17,
447
+ "train_batch_size": 48,
448
+ "trial_name": null,
449
+ "trial_params": null
450
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:144422285bc74c93e6a2efe4232e42180c06d4c332eb3559ca0e24f6d01f978c
3
+ size 5688