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Add application file
Browse files- app.py +45 -0
- my-bert-model/all_results.json +13 -0
- my-bert-model/config.json +27 -0
- my-bert-model/eval_results.json +8 -0
- my-bert-model/model.safetensors +3 -0
- my-bert-model/predict_results.txt +3264 -0
- my-bert-model/special_tokens_map.json +7 -0
- my-bert-model/tokenizer.json +0 -0
- my-bert-model/tokenizer_config.json +55 -0
- my-bert-model/train_results.json +8 -0
- my-bert-model/trainer_state.json +42 -0
- my-bert-model/training_args.bin +3 -0
- my-bert-model/vocab.txt +0 -0
- requirements.txt +2 -0
app.py
ADDED
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import string
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import gradio as gr
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import requests
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import torch
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from transformers import (
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AutoConfig,
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AutoModelForSequenceClassification,
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AutoTokenizer,
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)
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model_dir = "my-bert-model"
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config = AutoConfig.from_pretrained(model_dir, num_labels=2, finetuning_task="text-classification")
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tokenizer = AutoTokenizer.from_pretrained(model_dir)
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model = AutoModelForSequenceClassification.from_pretrained(model_dir, config=config)
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def inference(input_text):
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inputs = tokenizer.batch_encode_plus(
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[input_text],
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max_length=512,
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pad_to_max_length=True,
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truncation=True,
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padding="max_length",
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return_tensors="pt",
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)
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with torch.no_grad():
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logits = model(**inputs).logits
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predicted_class_id = logits.argmax().item()
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output = model.config.id2label[predicted_class_id]
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return output
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demo = gr.Interface(
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fn=inference,
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inputs=gr.Textbox(label="Input Text", scale=2, container=False),
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outputs=gr.Textbox(label="Output Label"),
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examples = [
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["My last two weather pics from the storm on August 2nd. People packed up real fast after the temp dropped and winds picked up.", 1],
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["Lying Clinton sinking! Donald Trump singing: Let's Make America Great Again!", 0],
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],
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title="Tutorial: BERT-based Text Classificatioin",
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)
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demo.launch(debug=True)
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my-bert-model/all_results.json
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{
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"epoch": 2.0,
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"eval_accuracy": 0.8424162836506894,
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"eval_loss": 0.3867124319076538,
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"eval_runtime": 24.5882,
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"eval_samples_per_second": 61.94,
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"eval_steps_per_second": 1.952,
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"total_flos": 3204692654284800.0,
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"train_loss": 0.40264760761360846,
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"train_runtime": 4707.1195,
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"train_samples_per_second": 2.588,
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"train_steps_per_second": 0.081
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}
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my-bert-model/config.json
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{
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.45.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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my-bert-model/eval_results.json
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{
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"epoch": 2.0,
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"eval_accuracy": 0.8424162836506894,
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"eval_loss": 0.3867124319076538,
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"eval_runtime": 24.5882,
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"eval_samples_per_second": 61.94,
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"eval_steps_per_second": 1.952
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}
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my-bert-model/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e6f7f82a3d6326b3d373c348783394240a3f8365be4f5ddcc3ad8588bdec48a8
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size 437958648
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my-bert-model/predict_results.txt
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|
1 |
+
index prediction
|
2 |
+
0 1
|
3 |
+
1 1
|
4 |
+
2 1
|
5 |
+
3 1
|
6 |
+
4 1
|
7 |
+
5 1
|
8 |
+
6 0
|
9 |
+
7 0
|
10 |
+
8 0
|
11 |
+
9 0
|
12 |
+
10 0
|
13 |
+
11 0
|
14 |
+
12 0
|
15 |
+
13 0
|
16 |
+
14 0
|
17 |
+
15 1
|
18 |
+
16 0
|
19 |
+
17 1
|
20 |
+
18 0
|
21 |
+
19 0
|
22 |
+
20 1
|
23 |
+
21 0
|
24 |
+
22 0
|
25 |
+
23 1
|
26 |
+
24 0
|
27 |
+
25 1
|
28 |
+
26 0
|
29 |
+
27 0
|
30 |
+
28 0
|
31 |
+
29 1
|
32 |
+
30 0
|
33 |
+
31 0
|
34 |
+
32 0
|
35 |
+
33 0
|
36 |
+
34 1
|
37 |
+
35 0
|
38 |
+
36 1
|
39 |
+
37 0
|
40 |
+
38 0
|
41 |
+
39 1
|
42 |
+
40 0
|
43 |
+
41 1
|
44 |
+
42 1
|
45 |
+
43 0
|
46 |
+
44 0
|
47 |
+
45 0
|
48 |
+
46 0
|
49 |
+
47 0
|
50 |
+
48 1
|
51 |
+
49 0
|
52 |
+
50 0
|
53 |
+
51 0
|
54 |
+
52 1
|
55 |
+
53 0
|
56 |
+
54 0
|
57 |
+
55 0
|
58 |
+
56 0
|
59 |
+
57 0
|
60 |
+
58 0
|
61 |
+
59 0
|
62 |
+
60 1
|
63 |
+
61 0
|
64 |
+
62 1
|
65 |
+
63 1
|
66 |
+
64 1
|
67 |
+
65 1
|
68 |
+
66 0
|
69 |
+
67 1
|
70 |
+
68 1
|
71 |
+
69 1
|
72 |
+
70 0
|
73 |
+
71 1
|
74 |
+
72 1
|
75 |
+
73 1
|
76 |
+
74 1
|
77 |
+
75 1
|
78 |
+
76 0
|
79 |
+
77 0
|
80 |
+
78 0
|
81 |
+
79 1
|
82 |
+
80 0
|
83 |
+
81 0
|
84 |
+
82 0
|
85 |
+
83 1
|
86 |
+
84 1
|
87 |
+
85 0
|
88 |
+
86 0
|
89 |
+
87 1
|
90 |
+
88 1
|
91 |
+
89 1
|
92 |
+
90 0
|
93 |
+
91 0
|
94 |
+
92 0
|
95 |
+
93 0
|
96 |
+
94 0
|
97 |
+
95 0
|
98 |
+
96 0
|
99 |
+
97 1
|
100 |
+
98 1
|
101 |
+
99 0
|
102 |
+
100 0
|
103 |
+
101 0
|
104 |
+
102 0
|
105 |
+
103 0
|
106 |
+
104 1
|
107 |
+
105 0
|
108 |
+
106 0
|
109 |
+
107 0
|
110 |
+
108 0
|
111 |
+
109 0
|
112 |
+
110 0
|
113 |
+
111 0
|
114 |
+
112 1
|
115 |
+
113 0
|
116 |
+
114 0
|
117 |
+
115 0
|
118 |
+
116 1
|
119 |
+
117 0
|
120 |
+
118 0
|
121 |
+
119 1
|
122 |
+
120 0
|
123 |
+
121 0
|
124 |
+
122 0
|
125 |
+
123 0
|
126 |
+
124 0
|
127 |
+
125 0
|
128 |
+
126 0
|
129 |
+
127 0
|
130 |
+
128 0
|
131 |
+
129 0
|
132 |
+
130 0
|
133 |
+
131 0
|
134 |
+
132 1
|
135 |
+
133 0
|
136 |
+
134 0
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|
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|
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|
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|
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|
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3260 1
|
3263 |
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3261 1
|
3264 |
+
3262 1
|
my-bert-model/special_tokens_map.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cls_token": "[CLS]",
|
3 |
+
"mask_token": "[MASK]",
|
4 |
+
"pad_token": "[PAD]",
|
5 |
+
"sep_token": "[SEP]",
|
6 |
+
"unk_token": "[UNK]"
|
7 |
+
}
|
my-bert-model/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
my-bert-model/tokenizer_config.json
ADDED
@@ -0,0 +1,55 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "[PAD]",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
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},
|
11 |
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"100": {
|
12 |
+
"content": "[UNK]",
|
13 |
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|
14 |
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|
15 |
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|
16 |
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"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"101": {
|
20 |
+
"content": "[CLS]",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"102": {
|
28 |
+
"content": "[SEP]",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"103": {
|
36 |
+
"content": "[MASK]",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"clean_up_tokenization_spaces": true,
|
45 |
+
"cls_token": "[CLS]",
|
46 |
+
"do_lower_case": true,
|
47 |
+
"mask_token": "[MASK]",
|
48 |
+
"model_max_length": 512,
|
49 |
+
"pad_token": "[PAD]",
|
50 |
+
"sep_token": "[SEP]",
|
51 |
+
"strip_accents": null,
|
52 |
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"tokenize_chinese_chars": true,
|
53 |
+
"tokenizer_class": "BertTokenizer",
|
54 |
+
"unk_token": "[UNK]"
|
55 |
+
}
|
my-bert-model/train_results.json
ADDED
@@ -0,0 +1,8 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"epoch": 2.0,
|
3 |
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"total_flos": 3204692654284800.0,
|
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"train_loss": 0.40264760761360846,
|
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"train_runtime": 4707.1195,
|
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"train_samples_per_second": 2.588,
|
7 |
+
"train_steps_per_second": 0.081
|
8 |
+
}
|
my-bert-model/trainer_state.json
ADDED
@@ -0,0 +1,42 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"best_metric": null,
|
3 |
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"best_model_checkpoint": null,
|
4 |
+
"epoch": 2.0,
|
5 |
+
"eval_steps": 500,
|
6 |
+
"global_step": 382,
|
7 |
+
"is_hyper_param_search": false,
|
8 |
+
"is_local_process_zero": true,
|
9 |
+
"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
11 |
+
{
|
12 |
+
"epoch": 2.0,
|
13 |
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"step": 382,
|
14 |
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"total_flos": 3204692654284800.0,
|
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"train_loss": 0.40264760761360846,
|
16 |
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"train_runtime": 4707.1195,
|
17 |
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"train_samples_per_second": 2.588,
|
18 |
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"train_steps_per_second": 0.081
|
19 |
+
}
|
20 |
+
],
|
21 |
+
"logging_steps": 500,
|
22 |
+
"max_steps": 382,
|
23 |
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"num_input_tokens_seen": 0,
|
24 |
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"num_train_epochs": 2,
|
25 |
+
"save_steps": 500,
|
26 |
+
"stateful_callbacks": {
|
27 |
+
"TrainerControl": {
|
28 |
+
"args": {
|
29 |
+
"should_epoch_stop": false,
|
30 |
+
"should_evaluate": false,
|
31 |
+
"should_log": false,
|
32 |
+
"should_save": true,
|
33 |
+
"should_training_stop": true
|
34 |
+
},
|
35 |
+
"attributes": {}
|
36 |
+
}
|
37 |
+
},
|
38 |
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"total_flos": 3204692654284800.0,
|
39 |
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"train_batch_size": 32,
|
40 |
+
"trial_name": null,
|
41 |
+
"trial_params": null
|
42 |
+
}
|
my-bert-model/training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:4a9fc1bfff3f4942540710caf4821c8f2f5e5f62fd0b39fb937a5d2804afdc38
|
3 |
+
size 5176
|
my-bert-model/vocab.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
requirements.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
transformers
|
2 |
+
torch
|