Model save
Browse files- README.md +7 -7
- all_results.json +7 -12
- train_results.json +7 -7
- trainer_state.json +262 -101
README.md
CHANGED
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
20 |
|
21 |
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the generator dataset.
|
22 |
It achieves the following results on the evaluation set:
|
23 |
-
- Loss: 1.
|
24 |
|
25 |
## Model description
|
26 |
|
@@ -48,22 +48,22 @@ The following hyperparameters were used during training:
|
|
48 |
- gradient_accumulation_steps: 2
|
49 |
- total_train_batch_size: 192
|
50 |
- total_eval_batch_size: 96
|
51 |
-
- optimizer: Use
|
52 |
- lr_scheduler_type: cosine
|
53 |
- lr_scheduler_warmup_ratio: 0.1
|
54 |
- num_epochs: 1
|
55 |
|
56 |
### Training results
|
57 |
|
58 |
-
| Training Loss | Epoch
|
59 |
-
|
60 |
-
|
|
61 |
|
62 |
|
63 |
### Framework versions
|
64 |
|
65 |
- PEFT 0.13.1.dev0
|
66 |
-
- Transformers 4.46.
|
67 |
-
- Pytorch 2.
|
68 |
- Datasets 3.1.0
|
69 |
- Tokenizers 0.20.3
|
|
|
20 |
|
21 |
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the generator dataset.
|
22 |
It achieves the following results on the evaluation set:
|
23 |
+
- Loss: 1.4864
|
24 |
|
25 |
## Model description
|
26 |
|
|
|
48 |
- gradient_accumulation_steps: 2
|
49 |
- total_train_batch_size: 192
|
50 |
- total_eval_batch_size: 96
|
51 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
52 |
- lr_scheduler_type: cosine
|
53 |
- lr_scheduler_warmup_ratio: 0.1
|
54 |
- num_epochs: 1
|
55 |
|
56 |
### Training results
|
57 |
|
58 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
59 |
+
|:-------------:|:-----:|:----:|:---------------:|
|
60 |
+
| 0.982 | 1.0 | 216 | 1.4864 |
|
61 |
|
62 |
|
63 |
### Framework versions
|
64 |
|
65 |
- PEFT 0.13.1.dev0
|
66 |
+
- Transformers 4.46.3
|
67 |
+
- Pytorch 2.3.1+cu121
|
68 |
- Datasets 3.1.0
|
69 |
- Tokenizers 0.20.3
|
all_results.json
CHANGED
@@ -1,14 +1,9 @@
|
|
1 |
{
|
2 |
-
"epoch": 0
|
3 |
-
"
|
4 |
-
"
|
5 |
-
"
|
6 |
-
"
|
7 |
-
"
|
8 |
-
"
|
9 |
-
"train_loss": 1.6186961426454431,
|
10 |
-
"train_runtime": 363.7432,
|
11 |
-
"train_samples": 51241,
|
12 |
-
"train_samples_per_second": 53.848,
|
13 |
-
"train_steps_per_second": 0.28
|
14 |
}
|
|
|
1 |
{
|
2 |
+
"epoch": 1.0,
|
3 |
+
"total_flos": 9.067486658407956e+17,
|
4 |
+
"train_loss": 1.0541787544886272,
|
5 |
+
"train_runtime": 774.5406,
|
6 |
+
"train_samples": 116368,
|
7 |
+
"train_samples_per_second": 53.491,
|
8 |
+
"train_steps_per_second": 0.279
|
|
|
|
|
|
|
|
|
|
|
9 |
}
|
train_results.json
CHANGED
@@ -1,9 +1,9 @@
|
|
1 |
{
|
2 |
-
"epoch": 0
|
3 |
-
"total_flos":
|
4 |
-
"train_loss": 1.
|
5 |
-
"train_runtime":
|
6 |
-
"train_samples":
|
7 |
-
"train_samples_per_second": 53.
|
8 |
-
"train_steps_per_second": 0.
|
9 |
}
|
|
|
1 |
{
|
2 |
+
"epoch": 1.0,
|
3 |
+
"total_flos": 9.067486658407956e+17,
|
4 |
+
"train_loss": 1.0541787544886272,
|
5 |
+
"train_runtime": 774.5406,
|
6 |
+
"train_samples": 116368,
|
7 |
+
"train_samples_per_second": 53.491,
|
8 |
+
"train_steps_per_second": 0.279
|
9 |
}
|
trainer_state.json
CHANGED
@@ -1,180 +1,341 @@
|
|
1 |
{
|
2 |
"best_metric": null,
|
3 |
"best_model_checkpoint": null,
|
4 |
-
"epoch": 0
|
5 |
"eval_steps": 500,
|
6 |
-
"global_step":
|
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.
|
13 |
-
"grad_norm": 2.
|
14 |
-
"learning_rate":
|
15 |
-
"loss":
|
16 |
"step": 1
|
17 |
},
|
18 |
{
|
19 |
-
"epoch": 0.
|
20 |
-
"grad_norm": 2.
|
21 |
-
"learning_rate":
|
22 |
-
"loss":
|
23 |
"step": 5
|
24 |
},
|
25 |
{
|
26 |
-
"epoch": 0.
|
27 |
-
"grad_norm":
|
28 |
-
"learning_rate":
|
29 |
-
"loss": 1.
|
30 |
"step": 10
|
31 |
},
|
32 |
{
|
33 |
-
"epoch": 0.
|
34 |
-
"grad_norm": 2.
|
35 |
-
"learning_rate": 0.
|
36 |
-
"loss": 1.
|
37 |
"step": 15
|
38 |
},
|
39 |
{
|
40 |
-
"epoch": 0.
|
41 |
-
"grad_norm":
|
42 |
-
"learning_rate": 0.
|
43 |
-
"loss": 1.
|
44 |
"step": 20
|
45 |
},
|
46 |
{
|
47 |
-
"epoch": 0.
|
48 |
-
"grad_norm": 1.
|
49 |
-
"learning_rate": 0.
|
50 |
-
"loss": 1.
|
51 |
"step": 25
|
52 |
},
|
53 |
{
|
54 |
-
"epoch": 0.
|
55 |
-
"grad_norm": 0.
|
56 |
-
"learning_rate": 0.
|
57 |
-
"loss": 1.
|
58 |
"step": 30
|
59 |
},
|
60 |
{
|
61 |
-
"epoch": 0.
|
62 |
-
"grad_norm": 0.
|
63 |
-
"learning_rate": 0.
|
64 |
-
"loss": 1.
|
65 |
"step": 35
|
66 |
},
|
67 |
{
|
68 |
-
"epoch": 0.
|
69 |
-
"grad_norm": 0.
|
70 |
-
"learning_rate": 0.
|
71 |
-
"loss": 1.
|
72 |
"step": 40
|
73 |
},
|
74 |
{
|
75 |
-
"epoch": 0.
|
76 |
-
"grad_norm": 0.
|
77 |
-
"learning_rate": 0.
|
78 |
-
"loss": 1.
|
79 |
"step": 45
|
80 |
},
|
81 |
{
|
82 |
-
"epoch": 0.
|
83 |
-
"grad_norm": 0.
|
84 |
-
"learning_rate": 0.
|
85 |
-
"loss": 1.
|
86 |
"step": 50
|
87 |
},
|
88 |
{
|
89 |
-
"epoch": 0.
|
90 |
-
"grad_norm": 0.
|
91 |
-
"learning_rate": 0.
|
92 |
-
"loss": 1.
|
93 |
"step": 55
|
94 |
},
|
95 |
{
|
96 |
-
"epoch": 0.
|
97 |
-
"grad_norm": 0.
|
98 |
-
"learning_rate":
|
99 |
-
"loss": 1.
|
100 |
"step": 60
|
101 |
},
|
102 |
{
|
103 |
-
"epoch": 0.
|
104 |
-
"grad_norm": 0.
|
105 |
-
"learning_rate":
|
106 |
-
"loss": 1.
|
107 |
"step": 65
|
108 |
},
|
109 |
{
|
110 |
-
"epoch": 0.
|
111 |
-
"grad_norm": 0.
|
112 |
-
"learning_rate":
|
113 |
-
"loss": 1.
|
114 |
"step": 70
|
115 |
},
|
116 |
{
|
117 |
-
"epoch": 0.
|
118 |
-
"grad_norm": 0.
|
119 |
-
"learning_rate":
|
120 |
-
"loss": 1.
|
121 |
"step": 75
|
122 |
},
|
123 |
{
|
124 |
-
"epoch": 0.
|
125 |
-
"grad_norm": 0.
|
126 |
-
"learning_rate":
|
127 |
-
"loss": 1.
|
128 |
"step": 80
|
129 |
},
|
130 |
{
|
131 |
-
"epoch": 0.
|
132 |
-
"grad_norm": 0.
|
133 |
-
"learning_rate":
|
134 |
-
"loss": 1.
|
135 |
"step": 85
|
136 |
},
|
137 |
{
|
138 |
-
"epoch": 0.
|
139 |
-
"grad_norm": 0.
|
140 |
-
"learning_rate":
|
141 |
-
"loss": 1.
|
142 |
"step": 90
|
143 |
},
|
144 |
{
|
145 |
-
"epoch": 0.
|
146 |
-
"grad_norm": 0.
|
147 |
-
"learning_rate":
|
148 |
-
"loss": 1.
|
149 |
"step": 95
|
150 |
},
|
151 |
{
|
152 |
-
"epoch": 0.
|
153 |
-
"grad_norm": 0.
|
154 |
-
"learning_rate":
|
155 |
-
"loss": 1.
|
156 |
"step": 100
|
157 |
},
|
158 |
{
|
159 |
-
"epoch": 0.
|
160 |
-
"
|
161 |
-
"
|
162 |
-
"
|
163 |
-
"
|
164 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
165 |
},
|
166 |
{
|
167 |
-
"epoch": 0
|
168 |
-
"step":
|
169 |
-
"total_flos":
|
170 |
-
"train_loss": 1.
|
171 |
-
"train_runtime":
|
172 |
-
"train_samples_per_second": 53.
|
173 |
-
"train_steps_per_second": 0.
|
174 |
}
|
175 |
],
|
176 |
"logging_steps": 5,
|
177 |
-
"max_steps":
|
178 |
"num_input_tokens_seen": 0,
|
179 |
"num_train_epochs": 1,
|
180 |
"save_steps": 100,
|
@@ -190,7 +351,7 @@
|
|
190 |
"attributes": {}
|
191 |
}
|
192 |
},
|
193 |
-
"total_flos":
|
194 |
"train_batch_size": 12,
|
195 |
"trial_name": null,
|
196 |
"trial_params": null
|
|
|
1 |
{
|
2 |
"best_metric": null,
|
3 |
"best_model_checkpoint": null,
|
4 |
+
"epoch": 1.0,
|
5 |
"eval_steps": 500,
|
6 |
+
"global_step": 216,
|
7 |
"is_hyper_param_search": false,
|
8 |
"is_local_process_zero": true,
|
9 |
"is_world_process_zero": true,
|
10 |
"log_history": [
|
11 |
{
|
12 |
+
"epoch": 0.004629629629629629,
|
13 |
+
"grad_norm": 2.620875597000122,
|
14 |
+
"learning_rate": 9.090909090909091e-06,
|
15 |
+
"loss": 1.5605,
|
16 |
"step": 1
|
17 |
},
|
18 |
{
|
19 |
+
"epoch": 0.023148148148148147,
|
20 |
+
"grad_norm": 2.674976348876953,
|
21 |
+
"learning_rate": 4.545454545454546e-05,
|
22 |
+
"loss": 1.5457,
|
23 |
"step": 5
|
24 |
},
|
25 |
{
|
26 |
+
"epoch": 0.046296296296296294,
|
27 |
+
"grad_norm": 2.3885157108306885,
|
28 |
+
"learning_rate": 9.090909090909092e-05,
|
29 |
+
"loss": 1.5006,
|
30 |
"step": 10
|
31 |
},
|
32 |
{
|
33 |
+
"epoch": 0.06944444444444445,
|
34 |
+
"grad_norm": 2.1752545833587646,
|
35 |
+
"learning_rate": 0.00013636363636363637,
|
36 |
+
"loss": 1.4093,
|
37 |
"step": 15
|
38 |
},
|
39 |
{
|
40 |
+
"epoch": 0.09259259259259259,
|
41 |
+
"grad_norm": 2.1516635417938232,
|
42 |
+
"learning_rate": 0.00018181818181818183,
|
43 |
+
"loss": 1.301,
|
44 |
"step": 20
|
45 |
},
|
46 |
{
|
47 |
+
"epoch": 0.11574074074074074,
|
48 |
+
"grad_norm": 1.6158533096313477,
|
49 |
+
"learning_rate": 0.0001998820159279591,
|
50 |
+
"loss": 1.195,
|
51 |
"step": 25
|
52 |
},
|
53 |
{
|
54 |
+
"epoch": 0.1388888888888889,
|
55 |
+
"grad_norm": 0.7115136384963989,
|
56 |
+
"learning_rate": 0.00019916201012264254,
|
57 |
+
"loss": 1.1232,
|
58 |
"step": 30
|
59 |
},
|
60 |
{
|
61 |
+
"epoch": 0.16203703703703703,
|
62 |
+
"grad_norm": 0.5917097926139832,
|
63 |
+
"learning_rate": 0.00019779225723955707,
|
64 |
+
"loss": 1.0867,
|
65 |
"step": 35
|
66 |
},
|
67 |
{
|
68 |
+
"epoch": 0.18518518518518517,
|
69 |
+
"grad_norm": 0.6770131587982178,
|
70 |
+
"learning_rate": 0.00019578173241879872,
|
71 |
+
"loss": 1.0683,
|
72 |
"step": 40
|
73 |
},
|
74 |
{
|
75 |
+
"epoch": 0.20833333333333334,
|
76 |
+
"grad_norm": 0.5598504543304443,
|
77 |
+
"learning_rate": 0.00019314360938108425,
|
78 |
+
"loss": 1.0576,
|
79 |
"step": 45
|
80 |
},
|
81 |
{
|
82 |
+
"epoch": 0.23148148148148148,
|
83 |
+
"grad_norm": 0.5453623533248901,
|
84 |
+
"learning_rate": 0.00018989517410853955,
|
85 |
+
"loss": 1.0375,
|
86 |
"step": 50
|
87 |
},
|
88 |
{
|
89 |
+
"epoch": 0.25462962962962965,
|
90 |
+
"grad_norm": 0.507411539554596,
|
91 |
+
"learning_rate": 0.00018605771158039253,
|
92 |
+
"loss": 1.0349,
|
93 |
"step": 55
|
94 |
},
|
95 |
{
|
96 |
+
"epoch": 0.2777777777777778,
|
97 |
+
"grad_norm": 0.5281575918197632,
|
98 |
+
"learning_rate": 0.0001816563663057211,
|
99 |
+
"loss": 1.0306,
|
100 |
"step": 60
|
101 |
},
|
102 |
{
|
103 |
+
"epoch": 0.30092592592592593,
|
104 |
+
"grad_norm": 0.49278953671455383,
|
105 |
+
"learning_rate": 0.00017671997756709863,
|
106 |
+
"loss": 1.0232,
|
107 |
"step": 65
|
108 |
},
|
109 |
{
|
110 |
+
"epoch": 0.32407407407407407,
|
111 |
+
"grad_norm": 0.44363367557525635,
|
112 |
+
"learning_rate": 0.00017128089045468294,
|
113 |
+
"loss": 1.0206,
|
114 |
"step": 70
|
115 |
},
|
116 |
{
|
117 |
+
"epoch": 0.3472222222222222,
|
118 |
+
"grad_norm": 0.4600500464439392,
|
119 |
+
"learning_rate": 0.00016537474392892528,
|
120 |
+
"loss": 1.0185,
|
121 |
"step": 75
|
122 |
},
|
123 |
{
|
124 |
+
"epoch": 0.37037037037037035,
|
125 |
+
"grad_norm": 0.4178927540779114,
|
126 |
+
"learning_rate": 0.00015904023730059228,
|
127 |
+
"loss": 1.0105,
|
128 |
"step": 80
|
129 |
},
|
130 |
{
|
131 |
+
"epoch": 0.39351851851851855,
|
132 |
+
"grad_norm": 0.5482760071754456,
|
133 |
+
"learning_rate": 0.000152318876658213,
|
134 |
+
"loss": 1.0164,
|
135 |
"step": 85
|
136 |
},
|
137 |
{
|
138 |
+
"epoch": 0.4166666666666667,
|
139 |
+
"grad_norm": 0.4235095679759979,
|
140 |
+
"learning_rate": 0.00014525470290445392,
|
141 |
+
"loss": 1.0151,
|
142 |
"step": 90
|
143 |
},
|
144 |
{
|
145 |
+
"epoch": 0.4398148148148148,
|
146 |
+
"grad_norm": 0.4932386875152588,
|
147 |
+
"learning_rate": 0.00013789400318343068,
|
148 |
+
"loss": 1.0081,
|
149 |
"step": 95
|
150 |
},
|
151 |
{
|
152 |
+
"epoch": 0.46296296296296297,
|
153 |
+
"grad_norm": 0.4402116537094116,
|
154 |
+
"learning_rate": 0.00013028500758979506,
|
155 |
+
"loss": 1.0094,
|
156 |
"step": 100
|
157 |
},
|
158 |
{
|
159 |
+
"epoch": 0.4861111111111111,
|
160 |
+
"grad_norm": 0.4497814476490021,
|
161 |
+
"learning_rate": 0.00012247757314687297,
|
162 |
+
"loss": 0.9996,
|
163 |
+
"step": 105
|
164 |
+
},
|
165 |
+
{
|
166 |
+
"epoch": 0.5092592592592593,
|
167 |
+
"grad_norm": 0.43658843636512756,
|
168 |
+
"learning_rate": 0.00011452285712454904,
|
169 |
+
"loss": 1.004,
|
170 |
+
"step": 110
|
171 |
+
},
|
172 |
+
{
|
173 |
+
"epoch": 0.5324074074074074,
|
174 |
+
"grad_norm": 0.4577714800834656,
|
175 |
+
"learning_rate": 0.00010647298183744359,
|
176 |
+
"loss": 0.9936,
|
177 |
+
"step": 115
|
178 |
+
},
|
179 |
+
{
|
180 |
+
"epoch": 0.5555555555555556,
|
181 |
+
"grad_norm": 0.44585293531417847,
|
182 |
+
"learning_rate": 9.838069311974986e-05,
|
183 |
+
"loss": 0.9953,
|
184 |
+
"step": 120
|
185 |
+
},
|
186 |
+
{
|
187 |
+
"epoch": 0.5787037037037037,
|
188 |
+
"grad_norm": 0.4536885619163513,
|
189 |
+
"learning_rate": 9.02990147145352e-05,
|
190 |
+
"loss": 0.9972,
|
191 |
+
"step": 125
|
192 |
+
},
|
193 |
+
{
|
194 |
+
"epoch": 0.6018518518518519,
|
195 |
+
"grad_norm": 0.4714517593383789,
|
196 |
+
"learning_rate": 8.228090084207774e-05,
|
197 |
+
"loss": 0.9963,
|
198 |
+
"step": 130
|
199 |
+
},
|
200 |
+
{
|
201 |
+
"epoch": 0.625,
|
202 |
+
"grad_norm": 0.45539769530296326,
|
203 |
+
"learning_rate": 7.437888922374276e-05,
|
204 |
+
"loss": 1.0039,
|
205 |
+
"step": 135
|
206 |
+
},
|
207 |
+
{
|
208 |
+
"epoch": 0.6481481481481481,
|
209 |
+
"grad_norm": 0.4661619961261749,
|
210 |
+
"learning_rate": 6.664475683491796e-05,
|
211 |
+
"loss": 0.996,
|
212 |
+
"step": 140
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"epoch": 0.6712962962962963,
|
216 |
+
"grad_norm": 0.4308771789073944,
|
217 |
+
"learning_rate": 5.9129180642644414e-05,
|
218 |
+
"loss": 0.9968,
|
219 |
+
"step": 145
|
220 |
+
},
|
221 |
+
{
|
222 |
+
"epoch": 0.6944444444444444,
|
223 |
+
"grad_norm": 0.42372000217437744,
|
224 |
+
"learning_rate": 5.1881405550919493e-05,
|
225 |
+
"loss": 0.997,
|
226 |
+
"step": 150
|
227 |
+
},
|
228 |
+
{
|
229 |
+
"epoch": 0.7175925925925926,
|
230 |
+
"grad_norm": 0.4466856122016907,
|
231 |
+
"learning_rate": 4.494892172941965e-05,
|
232 |
+
"loss": 0.997,
|
233 |
+
"step": 155
|
234 |
+
},
|
235 |
+
{
|
236 |
+
"epoch": 0.7407407407407407,
|
237 |
+
"grad_norm": 0.47718337178230286,
|
238 |
+
"learning_rate": 3.8377153439907266e-05,
|
239 |
+
"loss": 0.9932,
|
240 |
+
"step": 160
|
241 |
+
},
|
242 |
+
{
|
243 |
+
"epoch": 0.7638888888888888,
|
244 |
+
"grad_norm": 0.4494944214820862,
|
245 |
+
"learning_rate": 3.2209161399249674e-05,
|
246 |
+
"loss": 0.981,
|
247 |
+
"step": 165
|
248 |
+
},
|
249 |
+
{
|
250 |
+
"epoch": 0.7870370370370371,
|
251 |
+
"grad_norm": 0.4661237597465515,
|
252 |
+
"learning_rate": 2.6485360629279987e-05,
|
253 |
+
"loss": 0.988,
|
254 |
+
"step": 170
|
255 |
+
},
|
256 |
+
{
|
257 |
+
"epoch": 0.8101851851851852,
|
258 |
+
"grad_norm": 0.4337325394153595,
|
259 |
+
"learning_rate": 2.1243255642254578e-05,
|
260 |
+
"loss": 0.9888,
|
261 |
+
"step": 175
|
262 |
+
},
|
263 |
+
{
|
264 |
+
"epoch": 0.8333333333333334,
|
265 |
+
"grad_norm": 0.4312609136104584,
|
266 |
+
"learning_rate": 1.65171946970729e-05,
|
267 |
+
"loss": 0.9938,
|
268 |
+
"step": 180
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"epoch": 0.8564814814814815,
|
272 |
+
"grad_norm": 0.41870856285095215,
|
273 |
+
"learning_rate": 1.233814473646524e-05,
|
274 |
+
"loss": 0.9948,
|
275 |
+
"step": 185
|
276 |
+
},
|
277 |
+
{
|
278 |
+
"epoch": 0.8796296296296297,
|
279 |
+
"grad_norm": 0.47287535667419434,
|
280 |
+
"learning_rate": 8.733488479845997e-06,
|
281 |
+
"loss": 0.9905,
|
282 |
+
"step": 190
|
283 |
+
},
|
284 |
+
{
|
285 |
+
"epoch": 0.9027777777777778,
|
286 |
+
"grad_norm": 0.42414429783821106,
|
287 |
+
"learning_rate": 5.726845001356573e-06,
|
288 |
+
"loss": 0.9834,
|
289 |
+
"step": 195
|
290 |
+
},
|
291 |
+
{
|
292 |
+
"epoch": 0.9259259259259259,
|
293 |
+
"grad_norm": 0.4528570771217346,
|
294 |
+
"learning_rate": 3.3379149687388867e-06,
|
295 |
+
"loss": 0.9822,
|
296 |
+
"step": 200
|
297 |
+
},
|
298 |
+
{
|
299 |
+
"epoch": 0.9490740740740741,
|
300 |
+
"grad_norm": 0.4307001233100891,
|
301 |
+
"learning_rate": 1.5823515570925763e-06,
|
302 |
+
"loss": 0.9802,
|
303 |
+
"step": 205
|
304 |
+
},
|
305 |
+
{
|
306 |
+
"epoch": 0.9722222222222222,
|
307 |
+
"grad_norm": 0.42982199788093567,
|
308 |
+
"learning_rate": 4.7165788333860536e-07,
|
309 |
+
"loss": 0.9846,
|
310 |
+
"step": 210
|
311 |
+
},
|
312 |
+
{
|
313 |
+
"epoch": 0.9953703703703703,
|
314 |
+
"grad_norm": 0.4325573146343231,
|
315 |
+
"learning_rate": 1.3111633436779791e-08,
|
316 |
+
"loss": 0.982,
|
317 |
+
"step": 215
|
318 |
+
},
|
319 |
+
{
|
320 |
+
"epoch": 1.0,
|
321 |
+
"eval_loss": 1.4864426851272583,
|
322 |
+
"eval_runtime": 0.5986,
|
323 |
+
"eval_samples_per_second": 18.377,
|
324 |
+
"eval_steps_per_second": 1.671,
|
325 |
+
"step": 216
|
326 |
},
|
327 |
{
|
328 |
+
"epoch": 1.0,
|
329 |
+
"step": 216,
|
330 |
+
"total_flos": 9.067486658407956e+17,
|
331 |
+
"train_loss": 1.0541787544886272,
|
332 |
+
"train_runtime": 774.5406,
|
333 |
+
"train_samples_per_second": 53.491,
|
334 |
+
"train_steps_per_second": 0.279
|
335 |
}
|
336 |
],
|
337 |
"logging_steps": 5,
|
338 |
+
"max_steps": 216,
|
339 |
"num_input_tokens_seen": 0,
|
340 |
"num_train_epochs": 1,
|
341 |
"save_steps": 100,
|
|
|
351 |
"attributes": {}
|
352 |
}
|
353 |
},
|
354 |
+
"total_flos": 9.067486658407956e+17,
|
355 |
"train_batch_size": 12,
|
356 |
"trial_name": null,
|
357 |
"trial_params": null
|