ChenWu98 commited on
Commit
3ef6ac1
·
verified ·
1 Parent(s): dc18c9c

Model save

Browse files
Files changed (5) hide show
  1. README.md +7 -12
  2. all_results.json +9 -9
  3. eval_results.json +5 -5
  4. train_results.json +5 -5
  5. trainer_state.json +30 -22
README.md CHANGED
@@ -2,15 +2,9 @@
2
  license: mit
3
  library_name: peft
4
  tags:
5
- - alignment-handbook
6
  - trl
7
  - sft
8
  - generated_from_trainer
9
- - trl
10
- - sft
11
- - generated_from_trainer
12
- datasets:
13
- - ChenWu98/skills_metaphor_chat
14
  base_model: HuggingFaceH4/zephyr-7b-beta
15
  model-index:
16
  - name: skills_metaphor_chat-lora
@@ -22,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
22
 
23
  # skills_metaphor_chat-lora
24
 
25
- This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the ChenWu98/skills_metaphor_chat dataset.
26
  It achieves the following results on the evaluation set:
27
- - Loss: 0.2426
28
 
29
  ## Model description
30
 
@@ -48,18 +42,19 @@ The following hyperparameters were used during training:
48
  - eval_batch_size: 8
49
  - seed: 42
50
  - distributed_type: multi-GPU
51
- - gradient_accumulation_steps: 4
52
- - total_train_batch_size: 16
53
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
  - lr_scheduler_type: cosine
55
  - lr_scheduler_warmup_ratio: 0.1
56
- - num_epochs: 1.0
57
 
58
  ### Training results
59
 
60
  | Training Loss | Epoch | Step | Validation Loss |
61
  |:-------------:|:-----:|:----:|:---------------:|
62
- | 0.244 | 0.96 | 18 | 0.2426 |
 
63
 
64
 
65
  ### Framework versions
 
2
  license: mit
3
  library_name: peft
4
  tags:
 
5
  - trl
6
  - sft
7
  - generated_from_trainer
 
 
 
 
 
8
  base_model: HuggingFaceH4/zephyr-7b-beta
9
  model-index:
10
  - name: skills_metaphor_chat-lora
 
16
 
17
  # skills_metaphor_chat-lora
18
 
19
+ This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.2416
22
 
23
  ## Model description
24
 
 
42
  - eval_batch_size: 8
43
  - seed: 42
44
  - distributed_type: multi-GPU
45
+ - gradient_accumulation_steps: 8
46
+ - total_train_batch_size: 32
47
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
  - lr_scheduler_type: cosine
49
  - lr_scheduler_warmup_ratio: 0.1
50
+ - num_epochs: 2.0
51
 
52
  ### Training results
53
 
54
  | Training Loss | Epoch | Step | Validation Loss |
55
  |:-------------:|:-----:|:----:|:---------------:|
56
+ | 1.5756 | 0.96 | 9 | 0.2956 |
57
+ | 0.2474 | 1.92 | 18 | 0.2416 |
58
 
59
 
60
  ### Framework versions
all_results.json CHANGED
@@ -1,13 +1,13 @@
1
  {
2
- "epoch": 0.96,
3
- "eval_loss": 0.24263784289360046,
4
- "eval_runtime": 4.213,
5
  "eval_samples": 100,
6
- "eval_samples_per_second": 23.736,
7
- "eval_steps_per_second": 3.086,
8
- "train_loss": 0.6973882151974572,
9
- "train_runtime": 114.9152,
10
  "train_samples": 300,
11
- "train_samples_per_second": 2.611,
12
- "train_steps_per_second": 0.157
13
  }
 
1
  {
2
+ "epoch": 1.92,
3
+ "eval_loss": 0.24160662293434143,
4
+ "eval_runtime": 5.0894,
5
  "eval_samples": 100,
6
+ "eval_samples_per_second": 19.649,
7
+ "eval_steps_per_second": 2.554,
8
+ "train_loss": 0.692977637052536,
9
+ "train_runtime": 275.1049,
10
  "train_samples": 300,
11
+ "train_samples_per_second": 2.181,
12
+ "train_steps_per_second": 0.065
13
  }
eval_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
- "epoch": 0.96,
3
- "eval_loss": 0.24263784289360046,
4
- "eval_runtime": 4.213,
5
  "eval_samples": 100,
6
- "eval_samples_per_second": 23.736,
7
- "eval_steps_per_second": 3.086
8
  }
 
1
  {
2
+ "epoch": 1.92,
3
+ "eval_loss": 0.24160662293434143,
4
+ "eval_runtime": 5.0894,
5
  "eval_samples": 100,
6
+ "eval_samples_per_second": 19.649,
7
+ "eval_steps_per_second": 2.554
8
  }
train_results.json CHANGED
@@ -1,8 +1,8 @@
1
  {
2
- "epoch": 0.96,
3
- "train_loss": 0.6973882151974572,
4
- "train_runtime": 114.9152,
5
  "train_samples": 300,
6
- "train_samples_per_second": 2.611,
7
- "train_steps_per_second": 0.157
8
  }
 
1
  {
2
+ "epoch": 1.92,
3
+ "train_loss": 0.692977637052536,
4
+ "train_runtime": 275.1049,
5
  "train_samples": 300,
6
+ "train_samples_per_second": 2.181,
7
+ "train_steps_per_second": 0.065
8
  }
trainer_state.json CHANGED
@@ -1,7 +1,7 @@
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
- "epoch": 0.96,
5
  "eval_steps": 500,
6
  "global_step": 18,
7
  "is_hyper_param_search": false,
@@ -9,53 +9,61 @@
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
- "epoch": 0.05,
13
  "learning_rate": 0.0001,
14
- "loss": 2.1043,
15
  "step": 1
16
  },
17
  {
18
- "epoch": 0.27,
19
  "learning_rate": 0.00018314696123025454,
20
- "loss": 1.5726,
21
  "step": 5
22
  },
23
  {
24
- "epoch": 0.53,
 
 
 
 
 
 
 
 
25
  "learning_rate": 0.0001,
26
- "loss": 0.4372,
27
  "step": 10
28
  },
29
  {
30
- "epoch": 0.8,
31
  "learning_rate": 1.6853038769745467e-05,
32
- "loss": 0.244,
33
  "step": 15
34
  },
35
  {
36
- "epoch": 0.96,
37
- "eval_loss": 0.24263784289360046,
38
- "eval_runtime": 5.1186,
39
- "eval_samples_per_second": 19.536,
40
- "eval_steps_per_second": 2.54,
41
  "step": 18
42
  },
43
  {
44
- "epoch": 0.96,
45
  "step": 18,
46
- "total_flos": 9507448651776.0,
47
- "train_loss": 0.6973882151974572,
48
- "train_runtime": 114.9152,
49
- "train_samples_per_second": 2.611,
50
- "train_steps_per_second": 0.157
51
  }
52
  ],
53
  "logging_steps": 5,
54
  "max_steps": 18,
55
  "num_input_tokens_seen": 0,
56
- "num_train_epochs": 1,
57
  "save_steps": 500,
58
- "total_flos": 9507448651776.0,
59
  "train_batch_size": 4,
60
  "trial_name": null,
61
  "trial_params": null
 
1
  {
2
  "best_metric": null,
3
  "best_model_checkpoint": null,
4
+ "epoch": 1.92,
5
  "eval_steps": 500,
6
  "global_step": 18,
7
  "is_hyper_param_search": false,
 
9
  "is_world_process_zero": true,
10
  "log_history": [
11
  {
12
+ "epoch": 0.11,
13
  "learning_rate": 0.0001,
14
+ "loss": 2.0929,
15
  "step": 1
16
  },
17
  {
18
+ "epoch": 0.53,
19
  "learning_rate": 0.00018314696123025454,
20
+ "loss": 1.5756,
21
  "step": 5
22
  },
23
  {
24
+ "epoch": 0.96,
25
+ "eval_loss": 0.2955792546272278,
26
+ "eval_runtime": 7.0548,
27
+ "eval_samples_per_second": 14.175,
28
+ "eval_steps_per_second": 1.843,
29
+ "step": 9
30
+ },
31
+ {
32
+ "epoch": 1.07,
33
  "learning_rate": 0.0001,
34
+ "loss": 0.4344,
35
  "step": 10
36
  },
37
  {
38
+ "epoch": 1.6,
39
  "learning_rate": 1.6853038769745467e-05,
40
+ "loss": 0.2474,
41
  "step": 15
42
  },
43
  {
44
+ "epoch": 1.92,
45
+ "eval_loss": 0.24160662293434143,
46
+ "eval_runtime": 6.0397,
47
+ "eval_samples_per_second": 16.557,
48
+ "eval_steps_per_second": 2.152,
49
  "step": 18
50
  },
51
  {
52
+ "epoch": 1.92,
53
  "step": 18,
54
+ "total_flos": 19174999326720.0,
55
+ "train_loss": 0.692977637052536,
56
+ "train_runtime": 275.1049,
57
+ "train_samples_per_second": 2.181,
58
+ "train_steps_per_second": 0.065
59
  }
60
  ],
61
  "logging_steps": 5,
62
  "max_steps": 18,
63
  "num_input_tokens_seen": 0,
64
+ "num_train_epochs": 2,
65
  "save_steps": 500,
66
+ "total_flos": 19174999326720.0,
67
  "train_batch_size": 4,
68
  "trial_name": null,
69
  "trial_params": null