caffeinatedcherrychic commited on
Commit
d68a778
1 Parent(s): adc2281

Upload folder using huggingface_hub

Browse files
Files changed (49) hide show
  1. README.md +166 -0
  2. adapter_config.json +34 -0
  3. adapter_model.bin +3 -0
  4. checkpoint-13/README.md +202 -0
  5. checkpoint-13/adapter_config.json +34 -0
  6. checkpoint-13/adapter_model.safetensors +3 -0
  7. checkpoint-13/optimizer.pt +3 -0
  8. checkpoint-13/rng_state.pth +3 -0
  9. checkpoint-13/scheduler.pt +3 -0
  10. checkpoint-13/trainer_state.json +144 -0
  11. checkpoint-13/training_args.bin +3 -0
  12. checkpoint-26/README.md +202 -0
  13. checkpoint-26/adapter_config.json +34 -0
  14. checkpoint-26/adapter_model.safetensors +3 -0
  15. checkpoint-26/optimizer.pt +3 -0
  16. checkpoint-26/rng_state.pth +3 -0
  17. checkpoint-26/scheduler.pt +3 -0
  18. checkpoint-26/trainer_state.json +259 -0
  19. checkpoint-26/training_args.bin +3 -0
  20. checkpoint-39/README.md +202 -0
  21. checkpoint-39/adapter_config.json +34 -0
  22. checkpoint-39/adapter_model.safetensors +3 -0
  23. checkpoint-39/optimizer.pt +3 -0
  24. checkpoint-39/rng_state.pth +3 -0
  25. checkpoint-39/scheduler.pt +3 -0
  26. checkpoint-39/trainer_state.json +374 -0
  27. checkpoint-39/training_args.bin +3 -0
  28. checkpoint-52/README.md +202 -0
  29. checkpoint-52/adapter_config.json +34 -0
  30. checkpoint-52/adapter_model.safetensors +3 -0
  31. checkpoint-52/optimizer.pt +3 -0
  32. checkpoint-52/rng_state.pth +3 -0
  33. checkpoint-52/scheduler.pt +3 -0
  34. checkpoint-52/trainer_state.json +497 -0
  35. checkpoint-52/training_args.bin +3 -0
  36. config.json +40 -0
  37. merged/config.json +26 -0
  38. merged/generation_config.json +7 -0
  39. merged/pytorch_model-00001-of-00003.bin +3 -0
  40. merged/pytorch_model-00002-of-00003.bin +3 -0
  41. merged/pytorch_model-00003-of-00003.bin +3 -0
  42. merged/pytorch_model.bin.index.json +298 -0
  43. merged/special_tokens_map.json +24 -0
  44. merged/tokenizer.model +3 -0
  45. merged/tokenizer_config.json +44 -0
  46. runs/Apr09_08-29-36_gpu06.pri.dmog.alces.network/events.out.tfevents.1712647777.gpu06.pri.dmog.alces.network.30736.0 +3 -0
  47. special_tokens_map.json +24 -0
  48. tokenizer.model +3 -0
  49. tokenizer_config.json +44 -0
README.md ADDED
@@ -0,0 +1,166 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ library_name: peft
4
+ tags:
5
+ - generated_from_trainer
6
+ base_model: mistralai/Mistral-7B-v0.1
7
+ model-index:
8
+ - name: qlora-out
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
16
+ <details><summary>See axolotl config</summary>
17
+
18
+ axolotl version: `0.4.0`
19
+ ```yaml
20
+ base_model: mistralai/Mistral-7B-v0.1
21
+ model_type: MistralForCausalLM
22
+ tokenizer_type: LlamaTokenizer
23
+
24
+ load_in_8bit: false
25
+ load_in_4bit: true
26
+ strict: false
27
+
28
+ datasets:
29
+ - path: caffeinatedcherrychic/cidds-agg-balanced
30
+ type: alpaca
31
+ dataset_prepared_path: last_run_prepared
32
+ val_set_size: 0.1
33
+ output_dir: ./qlora-out
34
+
35
+ adapter: qlora
36
+ lora_model_dir:
37
+
38
+ sequence_len: 256
39
+ sample_packing: false
40
+ pad_to_sequence_len: true
41
+
42
+ lora_r: 32
43
+ lora_alpha: 64
44
+ lora_dropout: 0.05
45
+ lora_target_linear: true
46
+ lora_fan_in_fan_out:
47
+ lora_target_modules:
48
+ - gate_proj
49
+ - down_proj
50
+ - up_proj
51
+ - q_proj
52
+ - v_proj
53
+ - k_proj
54
+ - o_proj
55
+
56
+ wandb_project:
57
+ wandb_entity:
58
+ wandb_watch:
59
+ wandb_name:
60
+ wandb_log_model:
61
+
62
+ gradient_accumulation_steps: 4
63
+ micro_batch_size: 2
64
+ num_epochs: 5
65
+ optimizer: adamw_bnb_8bit
66
+ lr_scheduler: cosine
67
+ learning_rate: 0.0002
68
+
69
+ train_on_inputs: false
70
+ group_by_length: false
71
+ bf16: true
72
+ fp16: false
73
+ tf32: false
74
+
75
+ gradient_checkpointing: true
76
+ early_stopping_patience:
77
+ resume_from_checkpoint:
78
+ local_rank:
79
+ logging_steps: 1
80
+ xformers_attention:
81
+ flash_attention: true
82
+
83
+ loss_watchdog_threshold: 5.0
84
+ loss_watchdog_patience: 3
85
+
86
+ max_steps: 500
87
+ warmup_steps: 10
88
+ evals_per_epoch: 4
89
+ eval_table_size:
90
+ eval_max_new_tokens: 1
91
+ saves_per_epoch: 1
92
+ debug:
93
+ deepspeed:
94
+ weight_decay: 0.001
95
+ fsdp:
96
+ fsdp_config:
97
+ special_tokens:
98
+
99
+
100
+ ```
101
+
102
+ </details><br>
103
+
104
+ # qlora-out
105
+
106
+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
107
+ It achieves the following results on the evaluation set:
108
+ - Loss: 0.1465
109
+
110
+ ## Model description
111
+
112
+ More information needed
113
+
114
+ ## Intended uses & limitations
115
+
116
+ More information needed
117
+
118
+ ## Training and evaluation data
119
+
120
+ More information needed
121
+
122
+ ## Training procedure
123
+
124
+ ### Training hyperparameters
125
+
126
+ The following hyperparameters were used during training:
127
+ - learning_rate: 0.0002
128
+ - train_batch_size: 2
129
+ - eval_batch_size: 2
130
+ - seed: 42
131
+ - gradient_accumulation_steps: 4
132
+ - total_train_batch_size: 8
133
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
134
+ - lr_scheduler_type: cosine
135
+ - lr_scheduler_warmup_steps: 10
136
+ - training_steps: 62
137
+
138
+ ### Training results
139
+
140
+ | Training Loss | Epoch | Step | Validation Loss |
141
+ |:-------------:|:-----:|:----:|:---------------:|
142
+ | 6.6367 | 0.08 | 1 | 7.3009 |
143
+ | 2.3866 | 0.32 | 4 | 0.7138 |
144
+ | 0.948 | 0.64 | 8 | 1.0446 |
145
+ | 0.6822 | 0.96 | 12 | 1.3960 |
146
+ | 0.5222 | 1.28 | 16 | 0.9023 |
147
+ | 0.534 | 1.6 | 20 | 0.4847 |
148
+ | 0.4624 | 1.92 | 24 | 0.5740 |
149
+ | 0.7753 | 2.24 | 28 | 0.3772 |
150
+ | 0.3324 | 2.56 | 32 | 0.2937 |
151
+ | 0.1973 | 2.88 | 36 | 0.5675 |
152
+ | 0.0843 | 3.2 | 40 | 0.2360 |
153
+ | 0.3836 | 3.52 | 44 | 0.1397 |
154
+ | 0.0449 | 3.84 | 48 | 0.2801 |
155
+ | 0.2246 | 4.16 | 52 | 0.1946 |
156
+ | 0.229 | 4.48 | 56 | 0.1618 |
157
+ | 0.3073 | 4.8 | 60 | 0.1465 |
158
+
159
+
160
+ ### Framework versions
161
+
162
+ - PEFT 0.10.1.dev0
163
+ - Transformers 4.39.0.dev0
164
+ - Pytorch 2.1.2
165
+ - Datasets 2.18.0
166
+ - Tokenizers 0.15.0
adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 64,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "up_proj",
24
+ "k_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "down_proj",
28
+ "q_proj",
29
+ "v_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ef894f6daf736ab4a35fe0fba96204d34d3a179661233fc32771e92bcb515b0d
3
+ size 335706186
checkpoint-13/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: mistralai/Mistral-7B-v0.1
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
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]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.1.dev0
checkpoint-13/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 64,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "up_proj",
24
+ "k_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "down_proj",
28
+ "q_proj",
29
+ "v_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-13/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:72069b2abc2e8e408822bca99f6492f6272dff7f199d0afff420f28fdcde57ab
3
+ size 335604696
checkpoint-13/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aff099a7ecc6bc7c04d5f8fd80d2443dd9f492cb12877c91fe4ea29066d9dd08
3
+ size 168624724
checkpoint-13/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:74fd0abf3b25d5f521218bb97508206369e6984af4f556dd58b22d5dfbbb6425
3
+ size 14244
checkpoint-13/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8d3b6aff690f8457dc46d75813d9f660109e8ec63e2dc8cbf92e4d726c3a8a8c
3
+ size 1064
checkpoint-13/trainer_state.json ADDED
@@ -0,0 +1,144 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.04,
5
+ "eval_steps": 4,
6
+ "global_step": 13,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.08,
13
+ "grad_norm": 102.28898620605469,
14
+ "learning_rate": 2e-05,
15
+ "loss": 6.6367,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.08,
20
+ "eval_loss": 7.300913333892822,
21
+ "eval_runtime": 1.3523,
22
+ "eval_samples_per_second": 8.873,
23
+ "eval_steps_per_second": 4.437,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.16,
28
+ "grad_norm": 103.4541015625,
29
+ "learning_rate": 4e-05,
30
+ "loss": 7.0616,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.24,
35
+ "grad_norm": 67.47515869140625,
36
+ "learning_rate": 6e-05,
37
+ "loss": 4.686,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.32,
42
+ "grad_norm": 72.36919403076172,
43
+ "learning_rate": 8e-05,
44
+ "loss": 2.3866,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.32,
49
+ "eval_loss": 0.7137572169303894,
50
+ "eval_runtime": 1.3532,
51
+ "eval_samples_per_second": 8.868,
52
+ "eval_steps_per_second": 4.434,
53
+ "step": 4
54
+ },
55
+ {
56
+ "epoch": 0.4,
57
+ "grad_norm": 16.83085060119629,
58
+ "learning_rate": 0.0001,
59
+ "loss": 0.6844,
60
+ "step": 5
61
+ },
62
+ {
63
+ "epoch": 0.48,
64
+ "grad_norm": 25.897714614868164,
65
+ "learning_rate": 0.00012,
66
+ "loss": 0.914,
67
+ "step": 6
68
+ },
69
+ {
70
+ "epoch": 0.56,
71
+ "grad_norm": 18.89151382446289,
72
+ "learning_rate": 0.00014,
73
+ "loss": 0.63,
74
+ "step": 7
75
+ },
76
+ {
77
+ "epoch": 0.64,
78
+ "grad_norm": 27.15555763244629,
79
+ "learning_rate": 0.00016,
80
+ "loss": 0.948,
81
+ "step": 8
82
+ },
83
+ {
84
+ "epoch": 0.64,
85
+ "eval_loss": 1.0445994138717651,
86
+ "eval_runtime": 1.356,
87
+ "eval_samples_per_second": 8.85,
88
+ "eval_steps_per_second": 4.425,
89
+ "step": 8
90
+ },
91
+ {
92
+ "epoch": 0.72,
93
+ "grad_norm": 20.812381744384766,
94
+ "learning_rate": 0.00018,
95
+ "loss": 1.0285,
96
+ "step": 9
97
+ },
98
+ {
99
+ "epoch": 0.8,
100
+ "grad_norm": 56.3886604309082,
101
+ "learning_rate": 0.0002,
102
+ "loss": 1.3756,
103
+ "step": 10
104
+ },
105
+ {
106
+ "epoch": 0.88,
107
+ "grad_norm": 6.24803352355957,
108
+ "learning_rate": 0.00019981755542233177,
109
+ "loss": 0.5178,
110
+ "step": 11
111
+ },
112
+ {
113
+ "epoch": 0.96,
114
+ "grad_norm": 8.379430770874023,
115
+ "learning_rate": 0.0001992708874098054,
116
+ "loss": 0.6822,
117
+ "step": 12
118
+ },
119
+ {
120
+ "epoch": 0.96,
121
+ "eval_loss": 1.3959709405899048,
122
+ "eval_runtime": 1.3583,
123
+ "eval_samples_per_second": 8.835,
124
+ "eval_steps_per_second": 4.417,
125
+ "step": 12
126
+ },
127
+ {
128
+ "epoch": 1.04,
129
+ "grad_norm": 20.744348526000977,
130
+ "learning_rate": 0.00019836199069471437,
131
+ "loss": 1.3762,
132
+ "step": 13
133
+ }
134
+ ],
135
+ "logging_steps": 1,
136
+ "max_steps": 62,
137
+ "num_input_tokens_seen": 0,
138
+ "num_train_epochs": 6,
139
+ "save_steps": 13,
140
+ "total_flos": 1138234761412608.0,
141
+ "train_batch_size": 2,
142
+ "trial_name": null,
143
+ "trial_params": null
144
+ }
checkpoint-13/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66fede3f83b4ad6ce095e0aa09047d95bd4acc13170780f9e890d9d17d1bdace
3
+ size 5624
checkpoint-26/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: mistralai/Mistral-7B-v0.1
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
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]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.1.dev0
checkpoint-26/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 64,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "up_proj",
24
+ "k_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "down_proj",
28
+ "q_proj",
29
+ "v_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-26/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:387499c7736d8b7c5cab21843d9b986ad31e4777afa1c953e254a6b821622ab8
3
+ size 335604696
checkpoint-26/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c26885c89f597923fecf6d91cf382dfac6eeea66972dd286bb6316360fd0bb69
3
+ size 168624724
checkpoint-26/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:69726c1b60735ec075cbe9ef238868d0b5845ade6b93bfd60e810fcee5f233a5
3
+ size 14244
checkpoint-26/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c22f4d3e17b1ff1ac5db395ab84ba067bc34a07791275897d3efe0cf1944d439
3
+ size 1064
checkpoint-26/trainer_state.json ADDED
@@ -0,0 +1,259 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.08,
5
+ "eval_steps": 4,
6
+ "global_step": 26,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.08,
13
+ "grad_norm": 102.28898620605469,
14
+ "learning_rate": 2e-05,
15
+ "loss": 6.6367,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.08,
20
+ "eval_loss": 7.300913333892822,
21
+ "eval_runtime": 1.3523,
22
+ "eval_samples_per_second": 8.873,
23
+ "eval_steps_per_second": 4.437,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.16,
28
+ "grad_norm": 103.4541015625,
29
+ "learning_rate": 4e-05,
30
+ "loss": 7.0616,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.24,
35
+ "grad_norm": 67.47515869140625,
36
+ "learning_rate": 6e-05,
37
+ "loss": 4.686,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.32,
42
+ "grad_norm": 72.36919403076172,
43
+ "learning_rate": 8e-05,
44
+ "loss": 2.3866,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.32,
49
+ "eval_loss": 0.7137572169303894,
50
+ "eval_runtime": 1.3532,
51
+ "eval_samples_per_second": 8.868,
52
+ "eval_steps_per_second": 4.434,
53
+ "step": 4
54
+ },
55
+ {
56
+ "epoch": 0.4,
57
+ "grad_norm": 16.83085060119629,
58
+ "learning_rate": 0.0001,
59
+ "loss": 0.6844,
60
+ "step": 5
61
+ },
62
+ {
63
+ "epoch": 0.48,
64
+ "grad_norm": 25.897714614868164,
65
+ "learning_rate": 0.00012,
66
+ "loss": 0.914,
67
+ "step": 6
68
+ },
69
+ {
70
+ "epoch": 0.56,
71
+ "grad_norm": 18.89151382446289,
72
+ "learning_rate": 0.00014,
73
+ "loss": 0.63,
74
+ "step": 7
75
+ },
76
+ {
77
+ "epoch": 0.64,
78
+ "grad_norm": 27.15555763244629,
79
+ "learning_rate": 0.00016,
80
+ "loss": 0.948,
81
+ "step": 8
82
+ },
83
+ {
84
+ "epoch": 0.64,
85
+ "eval_loss": 1.0445994138717651,
86
+ "eval_runtime": 1.356,
87
+ "eval_samples_per_second": 8.85,
88
+ "eval_steps_per_second": 4.425,
89
+ "step": 8
90
+ },
91
+ {
92
+ "epoch": 0.72,
93
+ "grad_norm": 20.812381744384766,
94
+ "learning_rate": 0.00018,
95
+ "loss": 1.0285,
96
+ "step": 9
97
+ },
98
+ {
99
+ "epoch": 0.8,
100
+ "grad_norm": 56.3886604309082,
101
+ "learning_rate": 0.0002,
102
+ "loss": 1.3756,
103
+ "step": 10
104
+ },
105
+ {
106
+ "epoch": 0.88,
107
+ "grad_norm": 6.24803352355957,
108
+ "learning_rate": 0.00019981755542233177,
109
+ "loss": 0.5178,
110
+ "step": 11
111
+ },
112
+ {
113
+ "epoch": 0.96,
114
+ "grad_norm": 8.379430770874023,
115
+ "learning_rate": 0.0001992708874098054,
116
+ "loss": 0.6822,
117
+ "step": 12
118
+ },
119
+ {
120
+ "epoch": 0.96,
121
+ "eval_loss": 1.3959709405899048,
122
+ "eval_runtime": 1.3583,
123
+ "eval_samples_per_second": 8.835,
124
+ "eval_steps_per_second": 4.417,
125
+ "step": 12
126
+ },
127
+ {
128
+ "epoch": 1.04,
129
+ "grad_norm": 20.744348526000977,
130
+ "learning_rate": 0.00019836199069471437,
131
+ "loss": 1.3762,
132
+ "step": 13
133
+ },
134
+ {
135
+ "epoch": 1.12,
136
+ "grad_norm": 4.800480842590332,
137
+ "learning_rate": 0.0001970941817426052,
138
+ "loss": 0.5248,
139
+ "step": 14
140
+ },
141
+ {
142
+ "epoch": 1.2,
143
+ "grad_norm": 11.284302711486816,
144
+ "learning_rate": 0.00019547208665085457,
145
+ "loss": 0.8094,
146
+ "step": 15
147
+ },
148
+ {
149
+ "epoch": 1.28,
150
+ "grad_norm": 5.787976264953613,
151
+ "learning_rate": 0.0001935016242685415,
152
+ "loss": 0.5222,
153
+ "step": 16
154
+ },
155
+ {
156
+ "epoch": 1.28,
157
+ "eval_loss": 0.9023411870002747,
158
+ "eval_runtime": 1.3623,
159
+ "eval_samples_per_second": 8.808,
160
+ "eval_steps_per_second": 4.404,
161
+ "step": 16
162
+ },
163
+ {
164
+ "epoch": 1.36,
165
+ "grad_norm": 21.48629379272461,
166
+ "learning_rate": 0.00019118998459920902,
167
+ "loss": 0.8027,
168
+ "step": 17
169
+ },
170
+ {
171
+ "epoch": 1.44,
172
+ "grad_norm": 38.0982666015625,
173
+ "learning_rate": 0.000188545602565321,
174
+ "loss": 1.7772,
175
+ "step": 18
176
+ },
177
+ {
178
+ "epoch": 1.52,
179
+ "grad_norm": 10.824837684631348,
180
+ "learning_rate": 0.00018557812723014476,
181
+ "loss": 0.7737,
182
+ "step": 19
183
+ },
184
+ {
185
+ "epoch": 1.6,
186
+ "grad_norm": 9.1353120803833,
187
+ "learning_rate": 0.00018229838658936564,
188
+ "loss": 0.534,
189
+ "step": 20
190
+ },
191
+ {
192
+ "epoch": 1.6,
193
+ "eval_loss": 0.4847445785999298,
194
+ "eval_runtime": 1.3637,
195
+ "eval_samples_per_second": 8.799,
196
+ "eval_steps_per_second": 4.4,
197
+ "step": 20
198
+ },
199
+ {
200
+ "epoch": 1.68,
201
+ "grad_norm": 3.8411033153533936,
202
+ "learning_rate": 0.00017871834806090501,
203
+ "loss": 0.3201,
204
+ "step": 21
205
+ },
206
+ {
207
+ "epoch": 1.76,
208
+ "grad_norm": 23.888507843017578,
209
+ "learning_rate": 0.00017485107481711012,
210
+ "loss": 2.2541,
211
+ "step": 22
212
+ },
213
+ {
214
+ "epoch": 1.84,
215
+ "grad_norm": 8.5956392288208,
216
+ "learning_rate": 0.00017071067811865476,
217
+ "loss": 0.8177,
218
+ "step": 23
219
+ },
220
+ {
221
+ "epoch": 1.92,
222
+ "grad_norm": 3.825141191482544,
223
+ "learning_rate": 0.00016631226582407952,
224
+ "loss": 0.4624,
225
+ "step": 24
226
+ },
227
+ {
228
+ "epoch": 1.92,
229
+ "eval_loss": 0.5740255117416382,
230
+ "eval_runtime": 1.3655,
231
+ "eval_samples_per_second": 8.788,
232
+ "eval_steps_per_second": 4.394,
233
+ "step": 24
234
+ },
235
+ {
236
+ "epoch": 2.0,
237
+ "grad_norm": 3.558993101119995,
238
+ "learning_rate": 0.00016167188726285434,
239
+ "loss": 0.3714,
240
+ "step": 25
241
+ },
242
+ {
243
+ "epoch": 2.08,
244
+ "grad_norm": 11.759211540222168,
245
+ "learning_rate": 0.00015680647467311557,
246
+ "loss": 0.6562,
247
+ "step": 26
248
+ }
249
+ ],
250
+ "logging_steps": 1,
251
+ "max_steps": 62,
252
+ "num_input_tokens_seen": 0,
253
+ "num_train_epochs": 6,
254
+ "save_steps": 13,
255
+ "total_flos": 2276469522825216.0,
256
+ "train_batch_size": 2,
257
+ "trial_name": null,
258
+ "trial_params": null
259
+ }
checkpoint-26/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66fede3f83b4ad6ce095e0aa09047d95bd4acc13170780f9e890d9d17d1bdace
3
+ size 5624
checkpoint-39/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: mistralai/Mistral-7B-v0.1
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
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]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.1.dev0
checkpoint-39/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 64,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "up_proj",
24
+ "k_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "down_proj",
28
+ "q_proj",
29
+ "v_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-39/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:12b8939dee1c9d7c76fb429805ca8dd1be67417b78ad3ae2622ce37f2a7294d6
3
+ size 335604696
checkpoint-39/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:62c9a9efa8eced911795343502191b7b9044f8b5aa46a6f27343859276faacbc
3
+ size 168624724
checkpoint-39/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b83b87057617d19867b72bb4f1d7769198abfb127e1bef7a626c1e07b9dee3f2
3
+ size 14244
checkpoint-39/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3a8d987b7fe563f350e72415c21199e03eb1c8b092374967d449229a0b0fa9b1
3
+ size 1064
checkpoint-39/trainer_state.json ADDED
@@ -0,0 +1,374 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 3.12,
5
+ "eval_steps": 4,
6
+ "global_step": 39,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.08,
13
+ "grad_norm": 102.28898620605469,
14
+ "learning_rate": 2e-05,
15
+ "loss": 6.6367,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.08,
20
+ "eval_loss": 7.300913333892822,
21
+ "eval_runtime": 1.3523,
22
+ "eval_samples_per_second": 8.873,
23
+ "eval_steps_per_second": 4.437,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.16,
28
+ "grad_norm": 103.4541015625,
29
+ "learning_rate": 4e-05,
30
+ "loss": 7.0616,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.24,
35
+ "grad_norm": 67.47515869140625,
36
+ "learning_rate": 6e-05,
37
+ "loss": 4.686,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.32,
42
+ "grad_norm": 72.36919403076172,
43
+ "learning_rate": 8e-05,
44
+ "loss": 2.3866,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.32,
49
+ "eval_loss": 0.7137572169303894,
50
+ "eval_runtime": 1.3532,
51
+ "eval_samples_per_second": 8.868,
52
+ "eval_steps_per_second": 4.434,
53
+ "step": 4
54
+ },
55
+ {
56
+ "epoch": 0.4,
57
+ "grad_norm": 16.83085060119629,
58
+ "learning_rate": 0.0001,
59
+ "loss": 0.6844,
60
+ "step": 5
61
+ },
62
+ {
63
+ "epoch": 0.48,
64
+ "grad_norm": 25.897714614868164,
65
+ "learning_rate": 0.00012,
66
+ "loss": 0.914,
67
+ "step": 6
68
+ },
69
+ {
70
+ "epoch": 0.56,
71
+ "grad_norm": 18.89151382446289,
72
+ "learning_rate": 0.00014,
73
+ "loss": 0.63,
74
+ "step": 7
75
+ },
76
+ {
77
+ "epoch": 0.64,
78
+ "grad_norm": 27.15555763244629,
79
+ "learning_rate": 0.00016,
80
+ "loss": 0.948,
81
+ "step": 8
82
+ },
83
+ {
84
+ "epoch": 0.64,
85
+ "eval_loss": 1.0445994138717651,
86
+ "eval_runtime": 1.356,
87
+ "eval_samples_per_second": 8.85,
88
+ "eval_steps_per_second": 4.425,
89
+ "step": 8
90
+ },
91
+ {
92
+ "epoch": 0.72,
93
+ "grad_norm": 20.812381744384766,
94
+ "learning_rate": 0.00018,
95
+ "loss": 1.0285,
96
+ "step": 9
97
+ },
98
+ {
99
+ "epoch": 0.8,
100
+ "grad_norm": 56.3886604309082,
101
+ "learning_rate": 0.0002,
102
+ "loss": 1.3756,
103
+ "step": 10
104
+ },
105
+ {
106
+ "epoch": 0.88,
107
+ "grad_norm": 6.24803352355957,
108
+ "learning_rate": 0.00019981755542233177,
109
+ "loss": 0.5178,
110
+ "step": 11
111
+ },
112
+ {
113
+ "epoch": 0.96,
114
+ "grad_norm": 8.379430770874023,
115
+ "learning_rate": 0.0001992708874098054,
116
+ "loss": 0.6822,
117
+ "step": 12
118
+ },
119
+ {
120
+ "epoch": 0.96,
121
+ "eval_loss": 1.3959709405899048,
122
+ "eval_runtime": 1.3583,
123
+ "eval_samples_per_second": 8.835,
124
+ "eval_steps_per_second": 4.417,
125
+ "step": 12
126
+ },
127
+ {
128
+ "epoch": 1.04,
129
+ "grad_norm": 20.744348526000977,
130
+ "learning_rate": 0.00019836199069471437,
131
+ "loss": 1.3762,
132
+ "step": 13
133
+ },
134
+ {
135
+ "epoch": 1.12,
136
+ "grad_norm": 4.800480842590332,
137
+ "learning_rate": 0.0001970941817426052,
138
+ "loss": 0.5248,
139
+ "step": 14
140
+ },
141
+ {
142
+ "epoch": 1.2,
143
+ "grad_norm": 11.284302711486816,
144
+ "learning_rate": 0.00019547208665085457,
145
+ "loss": 0.8094,
146
+ "step": 15
147
+ },
148
+ {
149
+ "epoch": 1.28,
150
+ "grad_norm": 5.787976264953613,
151
+ "learning_rate": 0.0001935016242685415,
152
+ "loss": 0.5222,
153
+ "step": 16
154
+ },
155
+ {
156
+ "epoch": 1.28,
157
+ "eval_loss": 0.9023411870002747,
158
+ "eval_runtime": 1.3623,
159
+ "eval_samples_per_second": 8.808,
160
+ "eval_steps_per_second": 4.404,
161
+ "step": 16
162
+ },
163
+ {
164
+ "epoch": 1.36,
165
+ "grad_norm": 21.48629379272461,
166
+ "learning_rate": 0.00019118998459920902,
167
+ "loss": 0.8027,
168
+ "step": 17
169
+ },
170
+ {
171
+ "epoch": 1.44,
172
+ "grad_norm": 38.0982666015625,
173
+ "learning_rate": 0.000188545602565321,
174
+ "loss": 1.7772,
175
+ "step": 18
176
+ },
177
+ {
178
+ "epoch": 1.52,
179
+ "grad_norm": 10.824837684631348,
180
+ "learning_rate": 0.00018557812723014476,
181
+ "loss": 0.7737,
182
+ "step": 19
183
+ },
184
+ {
185
+ "epoch": 1.6,
186
+ "grad_norm": 9.1353120803833,
187
+ "learning_rate": 0.00018229838658936564,
188
+ "loss": 0.534,
189
+ "step": 20
190
+ },
191
+ {
192
+ "epoch": 1.6,
193
+ "eval_loss": 0.4847445785999298,
194
+ "eval_runtime": 1.3637,
195
+ "eval_samples_per_second": 8.799,
196
+ "eval_steps_per_second": 4.4,
197
+ "step": 20
198
+ },
199
+ {
200
+ "epoch": 1.68,
201
+ "grad_norm": 3.8411033153533936,
202
+ "learning_rate": 0.00017871834806090501,
203
+ "loss": 0.3201,
204
+ "step": 21
205
+ },
206
+ {
207
+ "epoch": 1.76,
208
+ "grad_norm": 23.888507843017578,
209
+ "learning_rate": 0.00017485107481711012,
210
+ "loss": 2.2541,
211
+ "step": 22
212
+ },
213
+ {
214
+ "epoch": 1.84,
215
+ "grad_norm": 8.5956392288208,
216
+ "learning_rate": 0.00017071067811865476,
217
+ "loss": 0.8177,
218
+ "step": 23
219
+ },
220
+ {
221
+ "epoch": 1.92,
222
+ "grad_norm": 3.825141191482544,
223
+ "learning_rate": 0.00016631226582407952,
224
+ "loss": 0.4624,
225
+ "step": 24
226
+ },
227
+ {
228
+ "epoch": 1.92,
229
+ "eval_loss": 0.5740255117416382,
230
+ "eval_runtime": 1.3655,
231
+ "eval_samples_per_second": 8.788,
232
+ "eval_steps_per_second": 4.394,
233
+ "step": 24
234
+ },
235
+ {
236
+ "epoch": 2.0,
237
+ "grad_norm": 3.558993101119995,
238
+ "learning_rate": 0.00016167188726285434,
239
+ "loss": 0.3714,
240
+ "step": 25
241
+ },
242
+ {
243
+ "epoch": 2.08,
244
+ "grad_norm": 11.759211540222168,
245
+ "learning_rate": 0.00015680647467311557,
246
+ "loss": 0.6562,
247
+ "step": 26
248
+ },
249
+ {
250
+ "epoch": 2.16,
251
+ "grad_norm": 96.2179183959961,
252
+ "learning_rate": 0.00015173378141776568,
253
+ "loss": 1.5141,
254
+ "step": 27
255
+ },
256
+ {
257
+ "epoch": 2.24,
258
+ "grad_norm": 31.022045135498047,
259
+ "learning_rate": 0.00014647231720437686,
260
+ "loss": 0.7753,
261
+ "step": 28
262
+ },
263
+ {
264
+ "epoch": 2.24,
265
+ "eval_loss": 0.3771994113922119,
266
+ "eval_runtime": 1.3676,
267
+ "eval_samples_per_second": 8.775,
268
+ "eval_steps_per_second": 4.387,
269
+ "step": 28
270
+ },
271
+ {
272
+ "epoch": 2.32,
273
+ "grad_norm": 3.5004501342773438,
274
+ "learning_rate": 0.0001410412805452757,
275
+ "loss": 0.2649,
276
+ "step": 29
277
+ },
278
+ {
279
+ "epoch": 2.4,
280
+ "grad_norm": 5.16464376449585,
281
+ "learning_rate": 0.00013546048870425356,
282
+ "loss": 0.171,
283
+ "step": 30
284
+ },
285
+ {
286
+ "epoch": 2.48,
287
+ "grad_norm": 25.634010314941406,
288
+ "learning_rate": 0.00012975030538552032,
289
+ "loss": 0.9172,
290
+ "step": 31
291
+ },
292
+ {
293
+ "epoch": 2.56,
294
+ "grad_norm": 7.102908134460449,
295
+ "learning_rate": 0.0001239315664287558,
296
+ "loss": 0.3324,
297
+ "step": 32
298
+ },
299
+ {
300
+ "epoch": 2.56,
301
+ "eval_loss": 0.29374203085899353,
302
+ "eval_runtime": 1.3678,
303
+ "eval_samples_per_second": 8.773,
304
+ "eval_steps_per_second": 4.387,
305
+ "step": 32
306
+ },
307
+ {
308
+ "epoch": 2.64,
309
+ "grad_norm": 6.236325263977051,
310
+ "learning_rate": 0.0001180255037813906,
311
+ "loss": 0.4932,
312
+ "step": 33
313
+ },
314
+ {
315
+ "epoch": 2.72,
316
+ "grad_norm": 4.445058345794678,
317
+ "learning_rate": 0.0001120536680255323,
318
+ "loss": 0.1284,
319
+ "step": 34
320
+ },
321
+ {
322
+ "epoch": 2.8,
323
+ "grad_norm": 6.94170618057251,
324
+ "learning_rate": 0.00010603784974222861,
325
+ "loss": 0.1547,
326
+ "step": 35
327
+ },
328
+ {
329
+ "epoch": 2.88,
330
+ "grad_norm": 5.656033039093018,
331
+ "learning_rate": 0.0001,
332
+ "loss": 0.1973,
333
+ "step": 36
334
+ },
335
+ {
336
+ "epoch": 2.88,
337
+ "eval_loss": 0.5674905180931091,
338
+ "eval_runtime": 1.3681,
339
+ "eval_samples_per_second": 8.771,
340
+ "eval_steps_per_second": 4.386,
341
+ "step": 36
342
+ },
343
+ {
344
+ "epoch": 2.96,
345
+ "grad_norm": 18.19667625427246,
346
+ "learning_rate": 9.396215025777139e-05,
347
+ "loss": 0.4884,
348
+ "step": 37
349
+ },
350
+ {
351
+ "epoch": 3.04,
352
+ "grad_norm": 17.964893341064453,
353
+ "learning_rate": 8.79463319744677e-05,
354
+ "loss": 0.5526,
355
+ "step": 38
356
+ },
357
+ {
358
+ "epoch": 3.12,
359
+ "grad_norm": 5.015590190887451,
360
+ "learning_rate": 8.197449621860943e-05,
361
+ "loss": 0.2116,
362
+ "step": 39
363
+ }
364
+ ],
365
+ "logging_steps": 1,
366
+ "max_steps": 62,
367
+ "num_input_tokens_seen": 0,
368
+ "num_train_epochs": 6,
369
+ "save_steps": 13,
370
+ "total_flos": 3414704284237824.0,
371
+ "train_batch_size": 2,
372
+ "trial_name": null,
373
+ "trial_params": null
374
+ }
checkpoint-39/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66fede3f83b4ad6ce095e0aa09047d95bd4acc13170780f9e890d9d17d1bdace
3
+ size 5624
checkpoint-52/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: mistralai/Mistral-7B-v0.1
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
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]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.1.dev0
checkpoint-52/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 64,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 32,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "up_proj",
24
+ "k_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "down_proj",
28
+ "q_proj",
29
+ "v_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-52/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61f543a16c2bbb11166292af99cbab42fa039c72766ce2da396aa279512c9d67
3
+ size 335604696
checkpoint-52/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bc05bf731a50997e7af44d91b701be1a9474180b446eef7cccd0a9bb6f49593f
3
+ size 168624724
checkpoint-52/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d215519440d74cb3c2d938d0a6d0dcc602aa66ebc4017b44adae1cc4c34379e9
3
+ size 14244
checkpoint-52/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:210095055e4e9fa9a08e2ee8a6ef338aebf6d1d63c758470bd2537cf069290da
3
+ size 1064
checkpoint-52/trainer_state.json ADDED
@@ -0,0 +1,497 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 0.19463467597961426,
3
+ "best_model_checkpoint": "./qlora-out/checkpoint-52",
4
+ "epoch": 4.16,
5
+ "eval_steps": 4,
6
+ "global_step": 52,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.08,
13
+ "grad_norm": 102.28898620605469,
14
+ "learning_rate": 2e-05,
15
+ "loss": 6.6367,
16
+ "step": 1
17
+ },
18
+ {
19
+ "epoch": 0.08,
20
+ "eval_loss": 7.300913333892822,
21
+ "eval_runtime": 1.3523,
22
+ "eval_samples_per_second": 8.873,
23
+ "eval_steps_per_second": 4.437,
24
+ "step": 1
25
+ },
26
+ {
27
+ "epoch": 0.16,
28
+ "grad_norm": 103.4541015625,
29
+ "learning_rate": 4e-05,
30
+ "loss": 7.0616,
31
+ "step": 2
32
+ },
33
+ {
34
+ "epoch": 0.24,
35
+ "grad_norm": 67.47515869140625,
36
+ "learning_rate": 6e-05,
37
+ "loss": 4.686,
38
+ "step": 3
39
+ },
40
+ {
41
+ "epoch": 0.32,
42
+ "grad_norm": 72.36919403076172,
43
+ "learning_rate": 8e-05,
44
+ "loss": 2.3866,
45
+ "step": 4
46
+ },
47
+ {
48
+ "epoch": 0.32,
49
+ "eval_loss": 0.7137572169303894,
50
+ "eval_runtime": 1.3532,
51
+ "eval_samples_per_second": 8.868,
52
+ "eval_steps_per_second": 4.434,
53
+ "step": 4
54
+ },
55
+ {
56
+ "epoch": 0.4,
57
+ "grad_norm": 16.83085060119629,
58
+ "learning_rate": 0.0001,
59
+ "loss": 0.6844,
60
+ "step": 5
61
+ },
62
+ {
63
+ "epoch": 0.48,
64
+ "grad_norm": 25.897714614868164,
65
+ "learning_rate": 0.00012,
66
+ "loss": 0.914,
67
+ "step": 6
68
+ },
69
+ {
70
+ "epoch": 0.56,
71
+ "grad_norm": 18.89151382446289,
72
+ "learning_rate": 0.00014,
73
+ "loss": 0.63,
74
+ "step": 7
75
+ },
76
+ {
77
+ "epoch": 0.64,
78
+ "grad_norm": 27.15555763244629,
79
+ "learning_rate": 0.00016,
80
+ "loss": 0.948,
81
+ "step": 8
82
+ },
83
+ {
84
+ "epoch": 0.64,
85
+ "eval_loss": 1.0445994138717651,
86
+ "eval_runtime": 1.356,
87
+ "eval_samples_per_second": 8.85,
88
+ "eval_steps_per_second": 4.425,
89
+ "step": 8
90
+ },
91
+ {
92
+ "epoch": 0.72,
93
+ "grad_norm": 20.812381744384766,
94
+ "learning_rate": 0.00018,
95
+ "loss": 1.0285,
96
+ "step": 9
97
+ },
98
+ {
99
+ "epoch": 0.8,
100
+ "grad_norm": 56.3886604309082,
101
+ "learning_rate": 0.0002,
102
+ "loss": 1.3756,
103
+ "step": 10
104
+ },
105
+ {
106
+ "epoch": 0.88,
107
+ "grad_norm": 6.24803352355957,
108
+ "learning_rate": 0.00019981755542233177,
109
+ "loss": 0.5178,
110
+ "step": 11
111
+ },
112
+ {
113
+ "epoch": 0.96,
114
+ "grad_norm": 8.379430770874023,
115
+ "learning_rate": 0.0001992708874098054,
116
+ "loss": 0.6822,
117
+ "step": 12
118
+ },
119
+ {
120
+ "epoch": 0.96,
121
+ "eval_loss": 1.3959709405899048,
122
+ "eval_runtime": 1.3583,
123
+ "eval_samples_per_second": 8.835,
124
+ "eval_steps_per_second": 4.417,
125
+ "step": 12
126
+ },
127
+ {
128
+ "epoch": 1.04,
129
+ "grad_norm": 20.744348526000977,
130
+ "learning_rate": 0.00019836199069471437,
131
+ "loss": 1.3762,
132
+ "step": 13
133
+ },
134
+ {
135
+ "epoch": 1.12,
136
+ "grad_norm": 4.800480842590332,
137
+ "learning_rate": 0.0001970941817426052,
138
+ "loss": 0.5248,
139
+ "step": 14
140
+ },
141
+ {
142
+ "epoch": 1.2,
143
+ "grad_norm": 11.284302711486816,
144
+ "learning_rate": 0.00019547208665085457,
145
+ "loss": 0.8094,
146
+ "step": 15
147
+ },
148
+ {
149
+ "epoch": 1.28,
150
+ "grad_norm": 5.787976264953613,
151
+ "learning_rate": 0.0001935016242685415,
152
+ "loss": 0.5222,
153
+ "step": 16
154
+ },
155
+ {
156
+ "epoch": 1.28,
157
+ "eval_loss": 0.9023411870002747,
158
+ "eval_runtime": 1.3623,
159
+ "eval_samples_per_second": 8.808,
160
+ "eval_steps_per_second": 4.404,
161
+ "step": 16
162
+ },
163
+ {
164
+ "epoch": 1.36,
165
+ "grad_norm": 21.48629379272461,
166
+ "learning_rate": 0.00019118998459920902,
167
+ "loss": 0.8027,
168
+ "step": 17
169
+ },
170
+ {
171
+ "epoch": 1.44,
172
+ "grad_norm": 38.0982666015625,
173
+ "learning_rate": 0.000188545602565321,
174
+ "loss": 1.7772,
175
+ "step": 18
176
+ },
177
+ {
178
+ "epoch": 1.52,
179
+ "grad_norm": 10.824837684631348,
180
+ "learning_rate": 0.00018557812723014476,
181
+ "loss": 0.7737,
182
+ "step": 19
183
+ },
184
+ {
185
+ "epoch": 1.6,
186
+ "grad_norm": 9.1353120803833,
187
+ "learning_rate": 0.00018229838658936564,
188
+ "loss": 0.534,
189
+ "step": 20
190
+ },
191
+ {
192
+ "epoch": 1.6,
193
+ "eval_loss": 0.4847445785999298,
194
+ "eval_runtime": 1.3637,
195
+ "eval_samples_per_second": 8.799,
196
+ "eval_steps_per_second": 4.4,
197
+ "step": 20
198
+ },
199
+ {
200
+ "epoch": 1.68,
201
+ "grad_norm": 3.8411033153533936,
202
+ "learning_rate": 0.00017871834806090501,
203
+ "loss": 0.3201,
204
+ "step": 21
205
+ },
206
+ {
207
+ "epoch": 1.76,
208
+ "grad_norm": 23.888507843017578,
209
+ "learning_rate": 0.00017485107481711012,
210
+ "loss": 2.2541,
211
+ "step": 22
212
+ },
213
+ {
214
+ "epoch": 1.84,
215
+ "grad_norm": 8.5956392288208,
216
+ "learning_rate": 0.00017071067811865476,
217
+ "loss": 0.8177,
218
+ "step": 23
219
+ },
220
+ {
221
+ "epoch": 1.92,
222
+ "grad_norm": 3.825141191482544,
223
+ "learning_rate": 0.00016631226582407952,
224
+ "loss": 0.4624,
225
+ "step": 24
226
+ },
227
+ {
228
+ "epoch": 1.92,
229
+ "eval_loss": 0.5740255117416382,
230
+ "eval_runtime": 1.3655,
231
+ "eval_samples_per_second": 8.788,
232
+ "eval_steps_per_second": 4.394,
233
+ "step": 24
234
+ },
235
+ {
236
+ "epoch": 2.0,
237
+ "grad_norm": 3.558993101119995,
238
+ "learning_rate": 0.00016167188726285434,
239
+ "loss": 0.3714,
240
+ "step": 25
241
+ },
242
+ {
243
+ "epoch": 2.08,
244
+ "grad_norm": 11.759211540222168,
245
+ "learning_rate": 0.00015680647467311557,
246
+ "loss": 0.6562,
247
+ "step": 26
248
+ },
249
+ {
250
+ "epoch": 2.16,
251
+ "grad_norm": 96.2179183959961,
252
+ "learning_rate": 0.00015173378141776568,
253
+ "loss": 1.5141,
254
+ "step": 27
255
+ },
256
+ {
257
+ "epoch": 2.24,
258
+ "grad_norm": 31.022045135498047,
259
+ "learning_rate": 0.00014647231720437686,
260
+ "loss": 0.7753,
261
+ "step": 28
262
+ },
263
+ {
264
+ "epoch": 2.24,
265
+ "eval_loss": 0.3771994113922119,
266
+ "eval_runtime": 1.3676,
267
+ "eval_samples_per_second": 8.775,
268
+ "eval_steps_per_second": 4.387,
269
+ "step": 28
270
+ },
271
+ {
272
+ "epoch": 2.32,
273
+ "grad_norm": 3.5004501342773438,
274
+ "learning_rate": 0.0001410412805452757,
275
+ "loss": 0.2649,
276
+ "step": 29
277
+ },
278
+ {
279
+ "epoch": 2.4,
280
+ "grad_norm": 5.16464376449585,
281
+ "learning_rate": 0.00013546048870425356,
282
+ "loss": 0.171,
283
+ "step": 30
284
+ },
285
+ {
286
+ "epoch": 2.48,
287
+ "grad_norm": 25.634010314941406,
288
+ "learning_rate": 0.00012975030538552032,
289
+ "loss": 0.9172,
290
+ "step": 31
291
+ },
292
+ {
293
+ "epoch": 2.56,
294
+ "grad_norm": 7.102908134460449,
295
+ "learning_rate": 0.0001239315664287558,
296
+ "loss": 0.3324,
297
+ "step": 32
298
+ },
299
+ {
300
+ "epoch": 2.56,
301
+ "eval_loss": 0.29374203085899353,
302
+ "eval_runtime": 1.3678,
303
+ "eval_samples_per_second": 8.773,
304
+ "eval_steps_per_second": 4.387,
305
+ "step": 32
306
+ },
307
+ {
308
+ "epoch": 2.64,
309
+ "grad_norm": 6.236325263977051,
310
+ "learning_rate": 0.0001180255037813906,
311
+ "loss": 0.4932,
312
+ "step": 33
313
+ },
314
+ {
315
+ "epoch": 2.72,
316
+ "grad_norm": 4.445058345794678,
317
+ "learning_rate": 0.0001120536680255323,
318
+ "loss": 0.1284,
319
+ "step": 34
320
+ },
321
+ {
322
+ "epoch": 2.8,
323
+ "grad_norm": 6.94170618057251,
324
+ "learning_rate": 0.00010603784974222861,
325
+ "loss": 0.1547,
326
+ "step": 35
327
+ },
328
+ {
329
+ "epoch": 2.88,
330
+ "grad_norm": 5.656033039093018,
331
+ "learning_rate": 0.0001,
332
+ "loss": 0.1973,
333
+ "step": 36
334
+ },
335
+ {
336
+ "epoch": 2.88,
337
+ "eval_loss": 0.5674905180931091,
338
+ "eval_runtime": 1.3681,
339
+ "eval_samples_per_second": 8.771,
340
+ "eval_steps_per_second": 4.386,
341
+ "step": 36
342
+ },
343
+ {
344
+ "epoch": 2.96,
345
+ "grad_norm": 18.19667625427246,
346
+ "learning_rate": 9.396215025777139e-05,
347
+ "loss": 0.4884,
348
+ "step": 37
349
+ },
350
+ {
351
+ "epoch": 3.04,
352
+ "grad_norm": 17.964893341064453,
353
+ "learning_rate": 8.79463319744677e-05,
354
+ "loss": 0.5526,
355
+ "step": 38
356
+ },
357
+ {
358
+ "epoch": 3.12,
359
+ "grad_norm": 5.015590190887451,
360
+ "learning_rate": 8.197449621860943e-05,
361
+ "loss": 0.2116,
362
+ "step": 39
363
+ },
364
+ {
365
+ "epoch": 3.2,
366
+ "grad_norm": 5.6883225440979,
367
+ "learning_rate": 7.606843357124426e-05,
368
+ "loss": 0.0843,
369
+ "step": 40
370
+ },
371
+ {
372
+ "epoch": 3.2,
373
+ "eval_loss": 0.2360386848449707,
374
+ "eval_runtime": 1.3667,
375
+ "eval_samples_per_second": 8.78,
376
+ "eval_steps_per_second": 4.39,
377
+ "step": 40
378
+ },
379
+ {
380
+ "epoch": 3.28,
381
+ "grad_norm": 6.636446475982666,
382
+ "learning_rate": 7.024969461447972e-05,
383
+ "loss": 0.1158,
384
+ "step": 41
385
+ },
386
+ {
387
+ "epoch": 3.36,
388
+ "grad_norm": 4.405576229095459,
389
+ "learning_rate": 6.453951129574644e-05,
390
+ "loss": 0.2755,
391
+ "step": 42
392
+ },
393
+ {
394
+ "epoch": 3.44,
395
+ "grad_norm": 1.6179524660110474,
396
+ "learning_rate": 5.8958719454724346e-05,
397
+ "loss": 0.0186,
398
+ "step": 43
399
+ },
400
+ {
401
+ "epoch": 3.52,
402
+ "grad_norm": 8.783114433288574,
403
+ "learning_rate": 5.3527682795623146e-05,
404
+ "loss": 0.3836,
405
+ "step": 44
406
+ },
407
+ {
408
+ "epoch": 3.52,
409
+ "eval_loss": 0.13969357311725616,
410
+ "eval_runtime": 1.3687,
411
+ "eval_samples_per_second": 8.767,
412
+ "eval_steps_per_second": 4.384,
413
+ "step": 44
414
+ },
415
+ {
416
+ "epoch": 3.6,
417
+ "grad_norm": 0.8835445046424866,
418
+ "learning_rate": 4.826621858223431e-05,
419
+ "loss": 0.0141,
420
+ "step": 45
421
+ },
422
+ {
423
+ "epoch": 3.68,
424
+ "grad_norm": 12.678099632263184,
425
+ "learning_rate": 4.3193525326884435e-05,
426
+ "loss": 0.6196,
427
+ "step": 46
428
+ },
429
+ {
430
+ "epoch": 3.76,
431
+ "grad_norm": 5.320870876312256,
432
+ "learning_rate": 3.832811273714569e-05,
433
+ "loss": 0.0948,
434
+ "step": 47
435
+ },
436
+ {
437
+ "epoch": 3.84,
438
+ "grad_norm": 2.7501108646392822,
439
+ "learning_rate": 3.36877341759205e-05,
440
+ "loss": 0.0449,
441
+ "step": 48
442
+ },
443
+ {
444
+ "epoch": 3.84,
445
+ "eval_loss": 0.2801015079021454,
446
+ "eval_runtime": 1.3706,
447
+ "eval_samples_per_second": 8.755,
448
+ "eval_steps_per_second": 4.378,
449
+ "step": 48
450
+ },
451
+ {
452
+ "epoch": 3.92,
453
+ "grad_norm": 4.41072940826416,
454
+ "learning_rate": 2.9289321881345254e-05,
455
+ "loss": 0.3026,
456
+ "step": 49
457
+ },
458
+ {
459
+ "epoch": 4.0,
460
+ "grad_norm": 1.2105910778045654,
461
+ "learning_rate": 2.514892518288988e-05,
462
+ "loss": 0.0152,
463
+ "step": 50
464
+ },
465
+ {
466
+ "epoch": 4.08,
467
+ "grad_norm": 4.502895355224609,
468
+ "learning_rate": 2.1281651939094992e-05,
469
+ "loss": 0.0629,
470
+ "step": 51
471
+ },
472
+ {
473
+ "epoch": 4.16,
474
+ "grad_norm": 6.058006286621094,
475
+ "learning_rate": 1.7701613410634365e-05,
476
+ "loss": 0.2246,
477
+ "step": 52
478
+ },
479
+ {
480
+ "epoch": 4.16,
481
+ "eval_loss": 0.19463467597961426,
482
+ "eval_runtime": 1.3725,
483
+ "eval_samples_per_second": 8.743,
484
+ "eval_steps_per_second": 4.372,
485
+ "step": 52
486
+ }
487
+ ],
488
+ "logging_steps": 1,
489
+ "max_steps": 62,
490
+ "num_input_tokens_seen": 0,
491
+ "num_train_epochs": 6,
492
+ "save_steps": 13,
493
+ "total_flos": 4552939045650432.0,
494
+ "train_batch_size": 2,
495
+ "trial_name": null,
496
+ "trial_params": null
497
+ }
checkpoint-52/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:66fede3f83b4ad6ce095e0aa09047d95bd4acc13170780f9e890d9d17d1bdace
3
+ size 5624
config.json ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "mistralai/Mistral-7B-v0.1",
3
+ "architectures": [
4
+ "MistralForCausalLM"
5
+ ],
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 4096,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 14336,
13
+ "max_position_embeddings": 32768,
14
+ "model_type": "mistral",
15
+ "num_attention_heads": 32,
16
+ "num_hidden_layers": 32,
17
+ "num_key_value_heads": 8,
18
+ "quantization_config": {
19
+ "_load_in_4bit": true,
20
+ "_load_in_8bit": false,
21
+ "bnb_4bit_compute_dtype": "bfloat16",
22
+ "bnb_4bit_quant_type": "nf4",
23
+ "bnb_4bit_use_double_quant": true,
24
+ "llm_int8_enable_fp32_cpu_offload": false,
25
+ "llm_int8_has_fp16_weight": false,
26
+ "llm_int8_skip_modules": null,
27
+ "llm_int8_threshold": 6.0,
28
+ "load_in_4bit": true,
29
+ "load_in_8bit": false,
30
+ "quant_method": "bitsandbytes"
31
+ },
32
+ "rms_norm_eps": 1e-05,
33
+ "rope_theta": 10000.0,
34
+ "sliding_window": 4096,
35
+ "tie_word_embeddings": false,
36
+ "torch_dtype": "bfloat16",
37
+ "transformers_version": "4.39.0.dev0",
38
+ "use_cache": false,
39
+ "vocab_size": 32000
40
+ }
merged/config.json ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "mistralai/Mistral-7B-v0.1",
3
+ "architectures": [
4
+ "MistralForCausalLM"
5
+ ],
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 4096,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 14336,
13
+ "max_position_embeddings": 32768,
14
+ "model_type": "mistral",
15
+ "num_attention_heads": 32,
16
+ "num_hidden_layers": 32,
17
+ "num_key_value_heads": 8,
18
+ "rms_norm_eps": 1e-05,
19
+ "rope_theta": 10000.0,
20
+ "sliding_window": 4096,
21
+ "tie_word_embeddings": false,
22
+ "torch_dtype": "bfloat16",
23
+ "transformers_version": "4.40.0.dev0",
24
+ "use_cache": false,
25
+ "vocab_size": 32000
26
+ }
merged/generation_config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 1,
4
+ "do_sample": true,
5
+ "eos_token_id": 2,
6
+ "transformers_version": "4.40.0.dev0"
7
+ }
merged/pytorch_model-00001-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cbefe924d88ca0cd30bc695b27d524c7a1e1e102eec3c44809d78da182784d6e
3
+ size 4943185632
merged/pytorch_model-00002-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:244c470b7b7bf63e652eeabed256b9e48b9b627ac0ea8423bf217435390a8e32
3
+ size 4999844744
merged/pytorch_model-00003-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6497299148ff6b197c49bd7046c4f481c732c2edb190f31af6780102b5fe911f
3
+ size 4540537414
merged/pytorch_model.bin.index.json ADDED
@@ -0,0 +1,298 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 14483464192
4
+ },
5
+ "weight_map": {
6
+ "lm_head.weight": "pytorch_model-00003-of-00003.bin",
7
+ "model.embed_tokens.weight": "pytorch_model-00001-of-00003.bin",
8
+ "model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
9
+ "model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
10
+ "model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
11
+ "model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
12
+ "model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
13
+ "model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
14
+ "model.layers.0.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
15
+ "model.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
16
+ "model.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
17
+ "model.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
18
+ "model.layers.1.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
19
+ "model.layers.1.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
20
+ "model.layers.1.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
21
+ "model.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
22
+ "model.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
23
+ "model.layers.1.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
24
+ "model.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
25
+ "model.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
26
+ "model.layers.10.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
27
+ "model.layers.10.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
28
+ "model.layers.10.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
29
+ "model.layers.10.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
30
+ "model.layers.10.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
31
+ "model.layers.10.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
32
+ "model.layers.10.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
33
+ "model.layers.10.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
34
+ "model.layers.10.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
35
+ "model.layers.11.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
36
+ "model.layers.11.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
37
+ "model.layers.11.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
38
+ "model.layers.11.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
39
+ "model.layers.11.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
40
+ "model.layers.11.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
41
+ "model.layers.11.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
42
+ "model.layers.11.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
43
+ "model.layers.11.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
44
+ "model.layers.12.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
45
+ "model.layers.12.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
46
+ "model.layers.12.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
47
+ "model.layers.12.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
48
+ "model.layers.12.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
49
+ "model.layers.12.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
50
+ "model.layers.12.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
51
+ "model.layers.12.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
52
+ "model.layers.12.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
53
+ "model.layers.13.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
54
+ "model.layers.13.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
55
+ "model.layers.13.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
56
+ "model.layers.13.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
57
+ "model.layers.13.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
58
+ "model.layers.13.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
59
+ "model.layers.13.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
60
+ "model.layers.13.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
61
+ "model.layers.13.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
62
+ "model.layers.14.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
63
+ "model.layers.14.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
64
+ "model.layers.14.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
65
+ "model.layers.14.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
66
+ "model.layers.14.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
67
+ "model.layers.14.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
68
+ "model.layers.14.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
69
+ "model.layers.14.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
70
+ "model.layers.14.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
71
+ "model.layers.15.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
72
+ "model.layers.15.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
73
+ "model.layers.15.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
74
+ "model.layers.15.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
75
+ "model.layers.15.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
76
+ "model.layers.15.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
77
+ "model.layers.15.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
78
+ "model.layers.15.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
79
+ "model.layers.15.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
80
+ "model.layers.16.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
81
+ "model.layers.16.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
82
+ "model.layers.16.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
83
+ "model.layers.16.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
84
+ "model.layers.16.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
85
+ "model.layers.16.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
86
+ "model.layers.16.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
87
+ "model.layers.16.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
88
+ "model.layers.16.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
89
+ "model.layers.17.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
90
+ "model.layers.17.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
91
+ "model.layers.17.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
92
+ "model.layers.17.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
93
+ "model.layers.17.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
94
+ "model.layers.17.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
95
+ "model.layers.17.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
96
+ "model.layers.17.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
97
+ "model.layers.17.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
98
+ "model.layers.18.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
99
+ "model.layers.18.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
100
+ "model.layers.18.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
101
+ "model.layers.18.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
102
+ "model.layers.18.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
103
+ "model.layers.18.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
104
+ "model.layers.18.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
105
+ "model.layers.18.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
106
+ "model.layers.18.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
107
+ "model.layers.19.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
108
+ "model.layers.19.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
109
+ "model.layers.19.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
110
+ "model.layers.19.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
111
+ "model.layers.19.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
112
+ "model.layers.19.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
113
+ "model.layers.19.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
114
+ "model.layers.19.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
115
+ "model.layers.19.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
116
+ "model.layers.2.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
117
+ "model.layers.2.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
118
+ "model.layers.2.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
119
+ "model.layers.2.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
120
+ "model.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
121
+ "model.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
122
+ "model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
123
+ "model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
124
+ "model.layers.2.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
125
+ "model.layers.20.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
126
+ "model.layers.20.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
127
+ "model.layers.20.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
128
+ "model.layers.20.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
129
+ "model.layers.20.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
130
+ "model.layers.20.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
131
+ "model.layers.20.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
132
+ "model.layers.20.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
133
+ "model.layers.20.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
134
+ "model.layers.21.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
135
+ "model.layers.21.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
136
+ "model.layers.21.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
137
+ "model.layers.21.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
138
+ "model.layers.21.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
139
+ "model.layers.21.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
140
+ "model.layers.21.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
141
+ "model.layers.21.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
142
+ "model.layers.21.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
143
+ "model.layers.22.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
144
+ "model.layers.22.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
145
+ "model.layers.22.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
146
+ "model.layers.22.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
147
+ "model.layers.22.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
148
+ "model.layers.22.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
149
+ "model.layers.22.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
150
+ "model.layers.22.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
151
+ "model.layers.22.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
152
+ "model.layers.23.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
153
+ "model.layers.23.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
154
+ "model.layers.23.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
155
+ "model.layers.23.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
156
+ "model.layers.23.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
157
+ "model.layers.23.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
158
+ "model.layers.23.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
159
+ "model.layers.23.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
160
+ "model.layers.23.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
161
+ "model.layers.24.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
162
+ "model.layers.24.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
163
+ "model.layers.24.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
164
+ "model.layers.24.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
165
+ "model.layers.24.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
166
+ "model.layers.24.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
167
+ "model.layers.24.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
168
+ "model.layers.24.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
169
+ "model.layers.24.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
170
+ "model.layers.25.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
171
+ "model.layers.25.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
172
+ "model.layers.25.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
173
+ "model.layers.25.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
174
+ "model.layers.25.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
175
+ "model.layers.25.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
176
+ "model.layers.25.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
177
+ "model.layers.25.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
178
+ "model.layers.25.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
179
+ "model.layers.26.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
180
+ "model.layers.26.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
181
+ "model.layers.26.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
182
+ "model.layers.26.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
183
+ "model.layers.26.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
184
+ "model.layers.26.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
185
+ "model.layers.26.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
186
+ "model.layers.26.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
187
+ "model.layers.26.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
188
+ "model.layers.27.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
189
+ "model.layers.27.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
190
+ "model.layers.27.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
191
+ "model.layers.27.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
192
+ "model.layers.27.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
193
+ "model.layers.27.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
194
+ "model.layers.27.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
195
+ "model.layers.27.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
196
+ "model.layers.27.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
197
+ "model.layers.28.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
198
+ "model.layers.28.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
199
+ "model.layers.28.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
200
+ "model.layers.28.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
201
+ "model.layers.28.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
202
+ "model.layers.28.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
203
+ "model.layers.28.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
204
+ "model.layers.28.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
205
+ "model.layers.28.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
206
+ "model.layers.29.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
207
+ "model.layers.29.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
208
+ "model.layers.29.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
209
+ "model.layers.29.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
210
+ "model.layers.29.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
211
+ "model.layers.29.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
212
+ "model.layers.29.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
213
+ "model.layers.29.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
214
+ "model.layers.29.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
215
+ "model.layers.3.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
216
+ "model.layers.3.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
217
+ "model.layers.3.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
218
+ "model.layers.3.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
219
+ "model.layers.3.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
220
+ "model.layers.3.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
221
+ "model.layers.3.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
222
+ "model.layers.3.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
223
+ "model.layers.3.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
224
+ "model.layers.30.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
225
+ "model.layers.30.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
226
+ "model.layers.30.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
227
+ "model.layers.30.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
228
+ "model.layers.30.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
229
+ "model.layers.30.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
230
+ "model.layers.30.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
231
+ "model.layers.30.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
232
+ "model.layers.30.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
233
+ "model.layers.31.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
234
+ "model.layers.31.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
235
+ "model.layers.31.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
236
+ "model.layers.31.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
237
+ "model.layers.31.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
238
+ "model.layers.31.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
239
+ "model.layers.31.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
240
+ "model.layers.31.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
241
+ "model.layers.31.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
242
+ "model.layers.4.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
243
+ "model.layers.4.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
244
+ "model.layers.4.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
245
+ "model.layers.4.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
246
+ "model.layers.4.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
247
+ "model.layers.4.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
248
+ "model.layers.4.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
249
+ "model.layers.4.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
250
+ "model.layers.4.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
251
+ "model.layers.5.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
252
+ "model.layers.5.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
253
+ "model.layers.5.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
254
+ "model.layers.5.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
255
+ "model.layers.5.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
256
+ "model.layers.5.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
257
+ "model.layers.5.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
258
+ "model.layers.5.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
259
+ "model.layers.5.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
260
+ "model.layers.6.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
261
+ "model.layers.6.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
262
+ "model.layers.6.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
263
+ "model.layers.6.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
264
+ "model.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
265
+ "model.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
266
+ "model.layers.6.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
267
+ "model.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
268
+ "model.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
269
+ "model.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
270
+ "model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
271
+ "model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
272
+ "model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
273
+ "model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
274
+ "model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
275
+ "model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
276
+ "model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
277
+ "model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
278
+ "model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
279
+ "model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
280
+ "model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
281
+ "model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
282
+ "model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
283
+ "model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
284
+ "model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
285
+ "model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
286
+ "model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
287
+ "model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
288
+ "model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
289
+ "model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
290
+ "model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
291
+ "model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
292
+ "model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
293
+ "model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
294
+ "model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
295
+ "model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
296
+ "model.norm.weight": "pytorch_model-00003-of-00003.bin"
297
+ }
298
+ }
merged/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
merged/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
merged/tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": true,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "additional_special_tokens": [],
32
+ "bos_token": "<s>",
33
+ "clean_up_tokenization_spaces": false,
34
+ "eos_token": "</s>",
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false,
43
+ "use_fast": true
44
+ }
runs/Apr09_08-29-36_gpu06.pri.dmog.alces.network/events.out.tfevents.1712647777.gpu06.pri.dmog.alces.network.30736.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b916e565a77dcb7d5bd53aba6f367407f84d56fd38e46a20f33d8b05d82f6ec7
3
+ size 23212
special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "</s>",
17
+ "unk_token": {
18
+ "content": "<unk>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
3
+ size 493443
tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "add_prefix_space": true,
5
+ "added_tokens_decoder": {
6
+ "0": {
7
+ "content": "<unk>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false,
12
+ "special": true
13
+ },
14
+ "1": {
15
+ "content": "<s>",
16
+ "lstrip": false,
17
+ "normalized": false,
18
+ "rstrip": false,
19
+ "single_word": false,
20
+ "special": true
21
+ },
22
+ "2": {
23
+ "content": "</s>",
24
+ "lstrip": false,
25
+ "normalized": false,
26
+ "rstrip": false,
27
+ "single_word": false,
28
+ "special": true
29
+ }
30
+ },
31
+ "additional_special_tokens": [],
32
+ "bos_token": "<s>",
33
+ "clean_up_tokenization_spaces": false,
34
+ "eos_token": "</s>",
35
+ "legacy": true,
36
+ "model_max_length": 1000000000000000019884624838656,
37
+ "pad_token": "</s>",
38
+ "sp_model_kwargs": {},
39
+ "spaces_between_special_tokens": false,
40
+ "tokenizer_class": "LlamaTokenizer",
41
+ "unk_token": "<unk>",
42
+ "use_default_system_prompt": false,
43
+ "use_fast": true
44
+ }