faridlazuarda commited on
Commit
2c85068
1 Parent(s): 4c2d0cb

Initial commit of latest checkpoint files

Browse files
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: CohereForAI/aya-101
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 0.10.0
adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "CohereForAI/aya-101",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.01,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 4,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "q",
24
+ "v"
25
+ ],
26
+ "task_type": "SEQ_CLS",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cececb099b3e2b9d2e272b5d46bfe07566c5242d08397e4b859854434d3c3140
3
+ size 18918496
optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:832db86ce0568dd67d71155967e4768687015a9b5556ece5e75f4f0e3b0b5244
3
+ size 37990394
rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:91ab3bca667cf29f3ea7c5e9867acbb2b3f66632e8425745ffc0e157fb4ac21a
3
+ size 14244
scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3639a21adec6316397ddf46df39adb14bf2c1acdddc7615711b1520a3e25eb1e
3
+ size 1064
trainer_state.json ADDED
@@ -0,0 +1,225 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.5068484544754028,
3
+ "best_model_checkpoint": "/mnt/beegfs/farid/mlora/outputs/xnli/aya-101/zh/rank4_lr5e-5/checkpoint-4000",
4
+ "epoch": 0.24445893089960888,
5
+ "eval_steps": 500,
6
+ "global_step": 6000,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.020371577574967405,
13
+ "grad_norm": 2.87671160697937,
14
+ "learning_rate": 4.166666666666667e-05,
15
+ "loss": 1.201,
16
+ "step": 500
17
+ },
18
+ {
19
+ "epoch": 0.020371577574967405,
20
+ "eval_accuracy": 0.3718875502008032,
21
+ "eval_f1": 0.3144388665500335,
22
+ "eval_loss": 1.0995594263076782,
23
+ "eval_runtime": 413.743,
24
+ "eval_samples_per_second": 6.018,
25
+ "eval_steps_per_second": 0.377,
26
+ "step": 500
27
+ },
28
+ {
29
+ "epoch": 0.04074315514993481,
30
+ "grad_norm": 9.780874252319336,
31
+ "learning_rate": 4.62962962962963e-05,
32
+ "loss": 1.0225,
33
+ "step": 1000
34
+ },
35
+ {
36
+ "epoch": 0.04074315514993481,
37
+ "eval_accuracy": 0.6277108433734939,
38
+ "eval_f1": 0.6294051779002606,
39
+ "eval_loss": 0.9010089039802551,
40
+ "eval_runtime": 411.7026,
41
+ "eval_samples_per_second": 6.048,
42
+ "eval_steps_per_second": 0.379,
43
+ "step": 1000
44
+ },
45
+ {
46
+ "epoch": 0.06111473272490222,
47
+ "grad_norm": 54.40706253051758,
48
+ "learning_rate": 4.166666666666667e-05,
49
+ "loss": 0.7434,
50
+ "step": 1500
51
+ },
52
+ {
53
+ "epoch": 0.06111473272490222,
54
+ "eval_accuracy": 0.748995983935743,
55
+ "eval_f1": 0.7514237869702255,
56
+ "eval_loss": 0.6406136155128479,
57
+ "eval_runtime": 411.3183,
58
+ "eval_samples_per_second": 6.054,
59
+ "eval_steps_per_second": 0.379,
60
+ "step": 1500
61
+ },
62
+ {
63
+ "epoch": 0.08148631029986962,
64
+ "grad_norm": 11.607203483581543,
65
+ "learning_rate": 3.7037037037037037e-05,
66
+ "loss": 0.6288,
67
+ "step": 2000
68
+ },
69
+ {
70
+ "epoch": 0.08148631029986962,
71
+ "eval_accuracy": 0.7738955823293173,
72
+ "eval_f1": 0.7758546821907705,
73
+ "eval_loss": 0.5777280926704407,
74
+ "eval_runtime": 411.4602,
75
+ "eval_samples_per_second": 6.052,
76
+ "eval_steps_per_second": 0.379,
77
+ "step": 2000
78
+ },
79
+ {
80
+ "epoch": 0.10185788787483703,
81
+ "grad_norm": 5.107800483703613,
82
+ "learning_rate": 3.240740740740741e-05,
83
+ "loss": 0.6186,
84
+ "step": 2500
85
+ },
86
+ {
87
+ "epoch": 0.10185788787483703,
88
+ "eval_accuracy": 0.7847389558232932,
89
+ "eval_f1": 0.7871483289805999,
90
+ "eval_loss": 0.5597745180130005,
91
+ "eval_runtime": 411.7146,
92
+ "eval_samples_per_second": 6.048,
93
+ "eval_steps_per_second": 0.379,
94
+ "step": 2500
95
+ },
96
+ {
97
+ "epoch": 0.12222946544980444,
98
+ "grad_norm": 7.775627136230469,
99
+ "learning_rate": 2.777777777777778e-05,
100
+ "loss": 0.5909,
101
+ "step": 3000
102
+ },
103
+ {
104
+ "epoch": 0.12222946544980444,
105
+ "eval_accuracy": 0.7963855421686747,
106
+ "eval_f1": 0.7956904592219637,
107
+ "eval_loss": 0.5284361839294434,
108
+ "eval_runtime": 411.1781,
109
+ "eval_samples_per_second": 6.056,
110
+ "eval_steps_per_second": 0.379,
111
+ "step": 3000
112
+ },
113
+ {
114
+ "epoch": 0.14260104302477183,
115
+ "grad_norm": 18.797571182250977,
116
+ "learning_rate": 2.314814814814815e-05,
117
+ "loss": 0.58,
118
+ "step": 3500
119
+ },
120
+ {
121
+ "epoch": 0.14260104302477183,
122
+ "eval_accuracy": 0.7891566265060241,
123
+ "eval_f1": 0.7909172071907363,
124
+ "eval_loss": 0.5231069922447205,
125
+ "eval_runtime": 412.124,
126
+ "eval_samples_per_second": 6.042,
127
+ "eval_steps_per_second": 0.379,
128
+ "step": 3500
129
+ },
130
+ {
131
+ "epoch": 0.16297262059973924,
132
+ "grad_norm": 5.233774185180664,
133
+ "learning_rate": 1.8518518518518518e-05,
134
+ "loss": 0.5752,
135
+ "step": 4000
136
+ },
137
+ {
138
+ "epoch": 0.16297262059973924,
139
+ "eval_accuracy": 0.8028112449799196,
140
+ "eval_f1": 0.8033343776283127,
141
+ "eval_loss": 0.5068484544754028,
142
+ "eval_runtime": 411.2741,
143
+ "eval_samples_per_second": 6.054,
144
+ "eval_steps_per_second": 0.379,
145
+ "step": 4000
146
+ },
147
+ {
148
+ "epoch": 0.18334419817470665,
149
+ "grad_norm": 5.612044334411621,
150
+ "learning_rate": 1.388888888888889e-05,
151
+ "loss": 0.5495,
152
+ "step": 4500
153
+ },
154
+ {
155
+ "epoch": 0.18334419817470665,
156
+ "eval_accuracy": 0.8016064257028113,
157
+ "eval_f1": 0.8027178095880526,
158
+ "eval_loss": 0.5132325887680054,
159
+ "eval_runtime": 411.4311,
160
+ "eval_samples_per_second": 6.052,
161
+ "eval_steps_per_second": 0.379,
162
+ "step": 4500
163
+ },
164
+ {
165
+ "epoch": 0.20371577574967406,
166
+ "grad_norm": 5.75107479095459,
167
+ "learning_rate": 9.259259259259259e-06,
168
+ "loss": 0.5594,
169
+ "step": 5000
170
+ },
171
+ {
172
+ "epoch": 0.20371577574967406,
173
+ "eval_accuracy": 0.8016064257028113,
174
+ "eval_f1": 0.802067784242174,
175
+ "eval_loss": 0.52597576379776,
176
+ "eval_runtime": 412.0059,
177
+ "eval_samples_per_second": 6.044,
178
+ "eval_steps_per_second": 0.379,
179
+ "step": 5000
180
+ },
181
+ {
182
+ "epoch": 0.22408735332464147,
183
+ "grad_norm": 4.854472637176514,
184
+ "learning_rate": 4.6296296296296296e-06,
185
+ "loss": 0.5561,
186
+ "step": 5500
187
+ },
188
+ {
189
+ "epoch": 0.22408735332464147,
190
+ "eval_accuracy": 0.8016064257028113,
191
+ "eval_f1": 0.8025734250007549,
192
+ "eval_loss": 0.5094338059425354,
193
+ "eval_runtime": 411.5334,
194
+ "eval_samples_per_second": 6.051,
195
+ "eval_steps_per_second": 0.379,
196
+ "step": 5500
197
+ },
198
+ {
199
+ "epoch": 0.24445893089960888,
200
+ "grad_norm": 6.345026016235352,
201
+ "learning_rate": 0.0,
202
+ "loss": 0.5454,
203
+ "step": 6000
204
+ },
205
+ {
206
+ "epoch": 0.24445893089960888,
207
+ "eval_accuracy": 0.804417670682731,
208
+ "eval_f1": 0.8051855538804084,
209
+ "eval_loss": 0.5121804475784302,
210
+ "eval_runtime": 411.4571,
211
+ "eval_samples_per_second": 6.052,
212
+ "eval_steps_per_second": 0.379,
213
+ "step": 6000
214
+ }
215
+ ],
216
+ "logging_steps": 500,
217
+ "max_steps": 6000,
218
+ "num_input_tokens_seen": 0,
219
+ "num_train_epochs": 1,
220
+ "save_steps": 500,
221
+ "total_flos": 8.03166870528e+17,
222
+ "train_batch_size": 16,
223
+ "trial_name": null,
224
+ "trial_params": null
225
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c103d55742ba673ae3b14f7d6f249482d41a4ce5bb9f8ae0c7bdb60ec1b3943f
3
+ size 5048