End of training
Browse files- README.md +88 -195
- model.safetensors +1 -1
README.md
CHANGED
@@ -1,199 +1,92 @@
|
|
1 |
---
|
2 |
library_name: transformers
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4 |
---
|
5 |
|
6 |
-
|
7 |
-
|
8 |
-
|
9 |
-
|
10 |
-
|
11 |
-
|
12 |
-
|
13 |
-
|
14 |
-
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
|
22 |
-
|
23 |
-
|
24 |
-
|
25 |
-
|
26 |
-
|
27 |
-
|
28 |
-
|
29 |
-
|
30 |
-
|
31 |
-
|
32 |
-
|
33 |
-
|
34 |
-
|
35 |
-
|
36 |
-
|
37 |
-
|
38 |
-
|
39 |
-
|
40 |
-
|
41 |
-
|
42 |
-
|
43 |
-
|
44 |
-
|
45 |
-
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
57 |
-
|
58 |
-
|
59 |
-
|
60 |
-
|
61 |
-
|
62 |
-
|
63 |
-
|
64 |
-
|
65 |
-
|
66 |
-
|
67 |
-
|
68 |
-
|
69 |
-
|
70 |
-
|
71 |
-
|
72 |
-
|
73 |
-
|
74 |
-
|
75 |
-
|
76 |
-
|
77 |
-
|
78 |
-
|
79 |
-
|
80 |
-
|
81 |
-
|
82 |
-
|
83 |
-
|
84 |
-
|
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]
|
|
|
1 |
---
|
2 |
library_name: transformers
|
3 |
+
license: mit
|
4 |
+
base_model: facebook/w2v-bert-2.0
|
5 |
+
tags:
|
6 |
+
- generated_from_trainer
|
7 |
+
metrics:
|
8 |
+
- wer
|
9 |
+
model-index:
|
10 |
+
- name: w2v-bert-2.0-lg-cv-5hr-v1
|
11 |
+
results: []
|
12 |
---
|
13 |
|
14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
15 |
+
should probably proofread and complete it, then remove this comment. -->
|
16 |
+
|
17 |
+
# w2v-bert-2.0-lg-cv-5hr-v1
|
18 |
+
|
19 |
+
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
|
20 |
+
It achieves the following results on the evaluation set:
|
21 |
+
- Loss: 2.8566
|
22 |
+
- Model Preparation Time: 0.0165
|
23 |
+
- Wer: 0.9775
|
24 |
+
- Cer: 0.8923
|
25 |
+
|
26 |
+
## Model description
|
27 |
+
|
28 |
+
More information needed
|
29 |
+
|
30 |
+
## Intended uses & limitations
|
31 |
+
|
32 |
+
More information needed
|
33 |
+
|
34 |
+
## Training and evaluation data
|
35 |
+
|
36 |
+
More information needed
|
37 |
+
|
38 |
+
## Training procedure
|
39 |
+
|
40 |
+
### Training hyperparameters
|
41 |
+
|
42 |
+
The following hyperparameters were used during training:
|
43 |
+
- learning_rate: 5e-05
|
44 |
+
- train_batch_size: 16
|
45 |
+
- eval_batch_size: 8
|
46 |
+
- seed: 42
|
47 |
+
- gradient_accumulation_steps: 2
|
48 |
+
- total_train_batch_size: 32
|
49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
50 |
+
- lr_scheduler_type: cosine
|
51 |
+
- lr_scheduler_warmup_ratio: 0.01
|
52 |
+
- num_epochs: 100
|
53 |
+
- mixed_precision_training: Native AMP
|
54 |
+
|
55 |
+
### Training results
|
56 |
+
|
57 |
+
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer |
|
58 |
+
|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
|
59 |
+
| 9.9607 | 0.9948 | 95 | 6.8754 | 0.0165 | 1.0 | 1.0 |
|
60 |
+
| 5.2586 | 2.0 | 191 | 4.0569 | 0.0165 | 1.0 | 1.0 |
|
61 |
+
| 3.4197 | 2.9948 | 286 | 3.0508 | 0.0165 | 1.0 | 1.0 |
|
62 |
+
| 2.9792 | 4.0 | 382 | 2.9586 | 0.0165 | 1.0 | 1.0 |
|
63 |
+
| 2.9646 | 4.9948 | 477 | 2.9354 | 0.0165 | 1.0 | 1.0 |
|
64 |
+
| 2.9169 | 6.0 | 573 | 2.9220 | 0.0165 | 1.0 | 1.0 |
|
65 |
+
| 2.9372 | 6.9948 | 668 | 2.9116 | 0.0165 | 1.0 | 1.0 |
|
66 |
+
| 2.8971 | 8.0 | 764 | 2.8998 | 0.0165 | 1.0 | 0.9811 |
|
67 |
+
| 2.918 | 8.9948 | 859 | 2.8893 | 0.0165 | 0.9983 | 0.9652 |
|
68 |
+
| 2.8795 | 10.0 | 955 | 2.8804 | 0.0165 | 0.9985 | 0.9534 |
|
69 |
+
| 2.9006 | 10.9948 | 1050 | 2.8683 | 0.0165 | 1.0 | 0.9048 |
|
70 |
+
| 2.8598 | 12.0 | 1146 | 2.8554 | 0.0165 | 1.0 | 0.9067 |
|
71 |
+
| 2.8776 | 12.9948 | 1241 | 2.8417 | 0.0165 | 1.0 | 0.8954 |
|
72 |
+
| 2.8393 | 14.0 | 1337 | 2.8407 | 0.0165 | 0.9970 | 0.9074 |
|
73 |
+
| 2.8637 | 14.9948 | 1432 | 2.8304 | 0.0165 | 0.9787 | 0.8824 |
|
74 |
+
| 2.8264 | 16.0 | 1528 | 2.8257 | 0.0165 | 0.9776 | 0.8934 |
|
75 |
+
| 2.846 | 16.9948 | 1623 | 2.8045 | 0.0165 | 1.0 | 0.8653 |
|
76 |
+
| 2.8001 | 18.0 | 1719 | 2.7907 | 0.0165 | 1.0022 | 0.8459 |
|
77 |
+
| 2.8103 | 18.9948 | 1814 | 2.7686 | 0.0165 | 0.9991 | 0.8579 |
|
78 |
+
| 2.7683 | 20.0 | 1910 | 2.7518 | 0.0165 | 0.9991 | 0.8534 |
|
79 |
+
| 2.7903 | 20.9948 | 2005 | 2.7481 | 0.0165 | 0.9980 | 0.8568 |
|
80 |
+
| 2.7561 | 22.0 | 2101 | 2.7468 | 0.0165 | 0.9991 | 0.8478 |
|
81 |
+
| 2.782 | 22.9948 | 2196 | 2.7383 | 0.0165 | 0.9978 | 0.8497 |
|
82 |
+
| 2.7473 | 24.0 | 2292 | 2.7345 | 0.0165 | 0.9993 | 0.8492 |
|
83 |
+
| 2.771 | 24.9948 | 2387 | 2.7175 | 0.0165 | 0.9970 | 0.8258 |
|
84 |
+
| 2.7049 | 26.0 | 2483 | 2.6822 | 0.0165 | 1.0260 | 0.7733 |
|
85 |
+
|
86 |
+
|
87 |
+
### Framework versions
|
88 |
+
|
89 |
+
- Transformers 4.44.2
|
90 |
+
- Pytorch 2.1.0+cu118
|
91 |
+
- Datasets 2.20.0
|
92 |
+
- Tokenizers 0.19.1
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 2322205912
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ec9d6214edd546fe9256b9f3578f5c39a4bcc432a5edb71ffc80473f8eadf053
|
3 |
size 2322205912
|