nbroad HF staff commited on
Commit
3110e3a
1 Parent(s): 3dc1a69

Training in progress, epoch 1

Browse files
README.md ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: microsoft/deberta-v3-small
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - nbroad/company_names
8
+ metrics:
9
+ - precision
10
+ - recall
11
+ - f1
12
+ - accuracy
13
+ model-index:
14
+ - name: deberta-v3-small-company-names
15
+ results:
16
+ - task:
17
+ name: Token Classification
18
+ type: token-classification
19
+ dataset:
20
+ name: nbroad/company_names
21
+ type: nbroad/company_names
22
+ metrics:
23
+ - name: Precision
24
+ type: precision
25
+ value: 0.7687575810084907
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+ - name: Recall
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+ type: recall
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+ value: 0.7920906980896268
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+ - name: F1
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+ type: f1
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+ value: 0.780249736194161
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+ - name: Accuracy
33
+ type: accuracy
34
+ value: 0.9766189637193916
35
+ ---
36
+
37
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
38
+ should probably proofread and complete it, then remove this comment. -->
39
+
40
+ # deberta-v3-small-company-names
41
+
42
+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the nbroad/company_names dataset.
43
+ It achieves the following results on the evaluation set:
44
+ - Loss: 0.0707
45
+ - Precision: 0.7688
46
+ - Recall: 0.7921
47
+ - F1: 0.7802
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+ - Accuracy: 0.9766
49
+
50
+ ## Model description
51
+
52
+ More information needed
53
+
54
+ ## Intended uses & limitations
55
+
56
+ More information needed
57
+
58
+ ## Training and evaluation data
59
+
60
+ More information needed
61
+
62
+ ## Training procedure
63
+
64
+ ### Training hyperparameters
65
+
66
+ The following hyperparameters were used during training:
67
+ - learning_rate: 8e-05
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+ - train_batch_size: 48
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
73
+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3.0
75
+
76
+ ### Training results
77
+
78
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
79
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0746 | 1.0 | 2126 | 0.0657 | 0.7415 | 0.7868 | 0.7635 | 0.9753 |
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+ | 0.0485 | 2.0 | 4252 | 0.0651 | 0.7631 | 0.7904 | 0.7765 | 0.9764 |
82
+ | 0.044 | 3.0 | 6378 | 0.0707 | 0.7688 | 0.7921 | 0.7802 | 0.9766 |
83
+
84
+
85
+ ### Framework versions
86
+
87
+ - Transformers 4.34.1
88
+ - Pytorch 2.0.1+cu117
89
+ - Datasets 2.16.1
90
+ - Tokenizers 0.14.1
added_tokens.json ADDED
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+ {
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+ }
all_results.json ADDED
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/deberta-v3-small",
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+ "DebertaV2ForTokenClassification"
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+ ],
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+ },
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pooler_hidden_size": 768,
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+ "p2c",
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.34.1",
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+ "type_vocab_size": 0,
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+ "vocab_size": 128100
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+ }
eval_results.json ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ "eval_steps_per_second": 189.225
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+ }
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5eb84817ac4a8647a830af4a80588a021daeee9c8150036f3a9c9c73f4faa66e
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+ size 565262061
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@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "rstrip": false,
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14
+ }
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+ }
spm.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ oid sha256:c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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+ size 2464616
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "split_by_punct": false,
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+ "tokenizer_class": "DebertaV2Tokenizer",
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+ "unk_token": "[UNK]",
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+ "vocab_type": "spm"
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+ }
train_results.json ADDED
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+ }
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